“One of the biggest bottlenecks in our workflow is bridging the gap between raw data and actionable insights fast enough to influence real-time decisions. With so many data sources and platforms, aligning everything into a clear, unified view takes time.”

– Jonathan Aufray of Growth Hackers

Why high‑quality data matters more than you think

Whether you’re an executive shaping strategy, an analyst wrangling spreadsheets, or a team member making daily calls, clean, high-quality data is the backbone of confident decision-making. This guide will walk you through practical ways to reduce errors, streamline your workflows, and turn raw, messy data into insights you can actually use. From automating deduplication to scaling reliable reporting processes – this is your playbook for better business outcomes.

What is data cleaning? (The real definition)

Data cleaning means finding and fixing errors, inconsistencies, and junk in your datasets so you can actually trust them for analysis and decision-making. It’s not just fixing typos – it’s about getting your data ready for complex queries, dashboards, and automated reports.

Here’s how data cleaning is different from related tasks:

Data cleaning

What it is:
Data cleaning is the process of fixing errors in your existing data. That includes:

• Removing duplicates
• Filling in missing values
• Standardizing formats (like dates, text capitalization, or number types)
• Resolving inconsistencies (e.g., “NY” vs. “New York”)
• Converting incompatible field types (convert text strings that hold numbers into numeric fields so calculations don’t break)

Why it matters:
Cleaning helps ensure accuracy and consistency. Without this step, your analysis can be skewed by bad inputs  –  leading to misleading reports or dashboards.

“I want to automate and simplify the process of cleaning and validating lead data when managing datasets with thousands of records, so I can minimize manual effort and reduce mistakes…”
  –  CRM Data Analyst, mid-sized business (Marissa S., Databox client)

Data cleansing

At first glance, “data cleaning” and “data cleansing” might sound like the same thing. But while both improve data quality, they’re not identical—and understanding the difference can help you choose the right approach for your needs.

What it is:

Data cleaning is all about quick fixes. It’s the process of automatically correcting obvious issues in your data—like removing duplicates, fixing typos, standardizing formats, and filling in missing values. Think of it as tidying up a messy room. It makes your data usable and reliable for day-to-day tasks.

Most teams automate this process so it runs continuously as new data flows in

Data cleansing takes it a step further. It’s a deeper, more strategic process that involves:

• Validating data against external sources
• Collaborating with domain experts to resolve inconsistencies
• Enriching and standardizing records
• Ensuring compliance with governance rules
• Exploring and consolidating variations in specific fields

Insycle puts it well: “A huge piece of the data management puzzle is understanding what you have in your database and cleansing it so it is uncluttered, formatted correctly, and standardized. But before you can begin fixing issues, you first have to identify what those issues are.”

Why both matter:

Data cleaning keeps your data functional—it’s like routine maintenance. Data cleansing is more like a full audit and tune-up. You’ll need both to make sure your data stays useful in the short term and trustworthy in the long term.

When you’re running a quick campaign report, basic cleaning might be enough. But when you’re building a strategy based on historical trends or predictive insights, you’ll want the confidence that comes from thorough cleansing.

Data preparation

What it is:
Data preparation goes a step further than cleaning. It includes cleaning plus:

• Merging data from multiple sources (e.g., CRM + payment data)
• Reshaping or restructuring datasets (e.g., pivoting rows to columns)
• Creating new fields (like calculated metrics or categories)
  Filtering or transforming data to align with business needs
  

Why it matters:
Preparation turns raw, cleaned data into a structure that’s usable for reporting, dashboards, or analytics tools. It’s how you build a curated “source of truth” across systems.

“We need a process for accurately matching and merging datasets using common identifiers – this underpins our ability to generate actionable business reports…”
  –  Business Intelligence Lead, E-commerce Retailer

Learn more about a Data Preparation framework here.

Data wrangling

What it is:
Data wrangling is the exploratory phase. It’s about:

• Investigating your data
• Identifying potential quality issues
• Deciding what needs to be cleaned, transformed, or restructured
  

It’s a mix of profiling, testing, and tweaking before formal cleaning or preparation happens.

Why it matters:
Think of wrangling as the detective work that informs your next steps. If you skip this step, you might miss deeper issues or apply the wrong fix.

“I’d rather go through and create the cleaning process myself and from there automate it once I understand the data…”

  –  Data Engineer, Reddit discussion

Each step builds on the last. Together, they help you create clean, reliable, analysis-ready datasets that power better decisions –  especially when working across messy tools like spreadsheets, CRMs, or marketing platforms.

The stakes are high. According to Harvard Business Review, only 3% of companies have data that meets basic quality standards. When bad inputs ripple through dashboards, high‑quality data becomes more than a technical nicety – it’s the difference between credible data analysis and expensive guesswork. Treat every dataset as an asset that must be protected, validated, and refined before you risk decisions – or dollars – on it.

The real cost of messy data

According to Gartner’s 2021 research, poor data quality costs the average organization about $15 million per year. But here’s the kicker – 60% of companies don’t even measure how much bad data costs them because they don’t track it.

Your analytics team is probably spending 45% of their time just preparing and cleaning data. That means your highest-paid people are doing data janitor work instead of finding insights that actually help the business.

If you’re at an agency, dirty data creates even more problems:

• Clients lose trust when reports have obvious mistakes
• You waste billable hours on repetitive cleaning tasks
• Results aren’t consistent across similar clients
• You can’t scale your services because everything requires manual work

Teams spend way too much time double-checking numbers, trying to figure out why reports don’t match, and explaining data problems in meetings instead of actually using insights to improve the business.

According to Anaconda’s 2020 State of Data Science Survey, companies report that their analytics teams spend the highest amount of time 45% doing data cleaning, 35% analysis and 20% for other tasks.

Data cleaning challenges by role

Different roles need different approaches to data cleaning. Here’s what each type of team member faces:

Executive leaders

You need trustworthy data for big decisions and measuring performance. Your biggest worry is data blind spots – when bad data makes you overconfident or hides real problems. When your KPI dashboards show conflicting numbers, it’s hard to make confident decisions about where to spend money and what strategies to pursue.

Data analysts and BI specialists

You deal with the messiest part – working directly with raw data from multiple sources. You have to balance automation with manual checking while dealing with tool limitations and systems that don’t play nice together.

“We need a process for accurately matching and merging datasets using common identifiers  –  this underpins our ability to generate actionable business reports from disparate data sources.”

 –  Business Intelligence Lead, E-commerce Retailer (Databox internal calls archives)

The biggest challenge? Merging datasets that have different structures, formats, and quality standards. Like when your CRM customer data doesn’t line up with transaction data from your e-commerce platform.

How to do it in Databox: In Databox, you can merge Datasets from different Views within the same Data Source (like HubSpot Contacts and Deals) or across multiple Sources (like HubSpot CRM and Shopify). Similar to SQL joins, this lets you explore more complex questions by connecting data across platforms.

Marketing and sales managers

You rely on clean data to measure performance and make strategic decisions. Data quality directly affects your ability to track KPIs, measure campaign effectiveness, and optimize marketing spend and sales processes.

Operations specialists

You work with data your team already cleaned, but you need to understand what happened to it. Clear documentation and consistent formats are crucial for your analytical work.

Essential techniques for cleaning data

Let’s get into the practical stuff. Here are the core techniques that handle most data quality issues:

1. Finding and removing duplicates automatically

Duplicate records typically appear as duplicate rows in a table or dataframe. You need repeatable logic to remove duplicate entries without wiping out legitimate multi‑touch interactions. There are two types to watch for:

Exact duplicates have identical values in all fields. These are easy to spot and remove.

Fuzzy duplicates are trickier – they’re variations in spelling, formatting, or data entry. Think customer names like “John Smith” vs “Jon Smith” or “J. Smith.”

Pro tip: Create composite keys that combine multiple fields to catch duplicates more accurately while keeping your queries running fast on large datasets.

2. Handling missing values intelligently

Don’t just delete everything with missing data – you’ll throw away valuable information. Here are better approaches:

Use averages for numerical data without strong patterns (like replacing missing sales amounts with the average sale amount).

Forward/backward fill works great for time series data where you can use the previous or next value to fill gaps. In SQL, COALESCE() and similar functions let you replace NULL values on‑the‑fly while keeping your query readable.

Apply business logic to determine what makes sense. Missing transaction amounts might be zero, while missing customer segments might get labeled “Unknown” for separate analysis.

3. Making everything consistent

Inconsistent formatting breaks joins and messes up grouping. Standardize these elements:

• Text (consistent capitalization, spacing, special characters)
• Dates (pick one format and stick with it)
• Categories (group similar values under consistent labels)
• Strip nonprinting characters (line breaks, zero‑width spaces) that silently break joins or visualizations

4. Dealing with outliers

Outliers can be real extreme values or data entry mistakes. These are values that sit far outside the normal distribution, like a misplaced decimal turning “99.00” into “9900.” Use both statistical methods (like standard deviations) and business rules (like “ages can’t be negative”) to identify them. Treat each outlier as a lead to investigate, not just something to delete.

Treatment options include capping values at reasonable limits, flagging suspicious data for manual review, or using transformations to reduce the impact of extreme values.

5. Ongoing quality monitoring

Set up automated checks that run when new data comes in:

• Track missing value percentages
• Monitor for business rule violations
• Watch duplicate rates over time

Using spell checking & text normalization to get from messy text to clean data

Free‑text columns such as open‑ended survey answers, support‑ticket notes, or product‑review blurbs are equal parts goldmine and grenade. One rogue emoji or a fat‑fingered brand name can blow up a join, skew a count, or flat‑out crash your CSV export. Treat text like any other data asset: profile it, clean it, and keep it on a tight leash.

Why it matters

• “Gooogle” vs. “Google” Two extra o’s and your pie chart suddenly shows a phantom competitor.
• “USA” vs. “usa” Case differences inflate “unique” values and wreck GROUP BYs.
• Smart quotes & emojis Fancy Unicode can choke SQL loaders or turn JSON into gibberish.

Three steps to cleaner text

1. Automated spell‑check with custom dictionaries
   Pipe your column through Hunspell, TextBlob, or Amazon Comprehend – but load a domain lexicon first so you don’t autocorrect “Shopify” into “Shopping.”
   
2. Normalize casing and Unicode
   Lowercase everything, strip diacritics, and swap curly quotes for straight ones before tokenizing or running sentiment analysis.
   
3. Tokenize & fuzzy‑match near‑duplicates
   Use Levenshtein distance or fuzzywuzzy to collapse “Jon Smith” and “John Smith,” or merge hashtag variants like #BlackFridayDeals and #blackfridaydeals.

Tool tips

• Python / Pandas

df['comment'] = (
    df['comment']
      .str.lower()
      .str.normalize('NFKD')  # strip accents
      .str.replace(r'[“”]', '"', regex=True)
)

• OpenRefine → Text facet → Cluster & Edit to spot near‑duplicates in seconds.
• SQL Use SOUNDEX() or Postgres trigram extensions for in‑database fuzzy matching.

Watch‑outs

• Over‑eager corrections “H&M” turning into “Ham” is not a glow‑up. Quarantine low‑confidence suggestions for manual review.
  
• Measure the impact After every sweep, rerun your profiling stats – null counts, distinct values, duplicate rates – to confirm you fixed more than you broke.

Building workflows that actually scale to deliver clean data

Effective data cleaning needs systematic workflows that can handle more data while maintaining quality. Here’s a four-phase approach:

Phase 1: Data profiling

Start by analyzing your datasets to spot patterns and quality issues. Review stats like record counts, missing data percentages, and unique values. Then document your findings to guide your cleaning rules.

Phase 2: Rule creation

Turn your profiling insights into automated cleaning procedures. Start with high-impact, simple rules like standardizing date formats or removing obvious duplicates. Add more complex rules gradually.

Phase 3: Testing and implementation

Run your cleaning rules on sample data first before applying them across the full dataset.

Phase 4: Monitoring

Keep an eye on how your cleaning rules perform as data sources and business needs change. Set up alerts for big changes in data quality or rule performance.

Key things to monitor:

• How long it takes to process each record
• What percentage of records get changed by each rule
• Error rates and rule failures
• Data quality scores before and after cleaning

How to do it in Databox: Leverage Datasets + Calculated Columns to build repeatable logic that prepares data before it reaches your dashboards. These transformations persist as new data flows in – no manual rework needed. For recurring processes, duplicate datasets templates for similar use cases.

Empower your team with clean, reliable data and make informed decisions with confidence.

Start Your Free 14-Day Trial with Databox – No credit card required

Tools that actually work

Different tools are good at different things. Here’s what works best for various scenarios:

Business Intelligence platforms

Many BI tools now include cleaning features:

• Tableau Prep: Visual data preparation with drag-and-drop cleaning
• Power BI with Power Query: Data transformation during import
• Looker: Data transformation during query execution
• Databox: Goes beyond dashboarding with its Advanced Analytics capabilities:
  • Dataset Software: Combine multiple data sources into unified, clean datasets.
  • Calculated Metrics: Create custom formulas and logic directly in the UI – no code required.
  • Filtering and Transformation: Apply rules to cleanse, categorize, or segment data before it reaches your reports.
  • Query-based Visualization: Use SQL-like dataset queries to refine your data pipeline in real-time.
  • Automated Data Sync: Ensure that your cleaned data is always up to date across sources like HubSpot, Google Analytics, CRMs, and more.

Explore all features → Databox Advanced Analytics

Open-source solutions

For flexibility and customization:

• OpenRefine: Great for interactive cleaning with smart duplicate detection
• Python libraries (Pandas, NumPy): Programmatic cleaning with machine learning
• R packages (dplyr, tidyr): Statistical approaches to missing data

AI-powered tools

The newest category uses machine learning to spot issues:

• Trifacta Wrangler: Uses AI to find inconsistencies and suggest fixes
• TIBCO Clarity: Cloud-based cleaning with tons of data source connections

SQL for data cleaning

SQL is powerful for cleaning because it:

• Works directly on your data without moving it around
• Handles large datasets efficiently
• Creates reproducible, shareable cleaning operations
• Integrates with your existing database setup

SQL is especially good for removing duplicates, filling missing values with business logic, and running validation checks that can be automated and scheduled.

How to do it in Databox: With no-code Dataset Builder, create calculated fields, apply filters, group data, and merge multiple sources. This gives your team SQL-like control over transformation logic – without writing any code.

Agency vs. internal team approaches

Agency use cases

You face unique challenges with multiple client datasets. Each client has different data structures, quality standards, and business rules.

Focus on:

• Creating reusable transformation templates
• Building libraries of cleaning procedures for common situations
• Preventing cross-client data contamination
• Documenting common issues by industry or platform type

Internal teams use cases

You work with more consistent data sources but need to balance different departmental needs.

Focus on:

• Accommodating different analytical needs across departments
• Balancing individual team requirements with organizational standards
• Implementing monitoring to prevent quality regression
• Creating shared dataset governance

“Automating this process would free up our team to focus more on strategy and creativity, not data wrangling.”

–  Jonathan Aufray,Growth Hackers

Measuring success

Track these metrics to show the value of your data cleaning efforts:

Data quality metrics

• Accuracy rates
• Completeness levels
• Consistency scores
• Timeliness of updates

Time savings

• Hours saved through automation
• Reduction in manual cleaning tasks
• Fewer data-related support requests
• Less time spent on analysis rework

ROI calculation

ROI = (Time Savings + Error Prevention + Better Decisions) ÷ (Tool Costs + Setup + Maintenance)

Organizations typically see a return on investment ranging from 5:1 to 15:1 from data cleansing initiatives, with some companies achieving ROI exceeding 500% within two years.

Common mistakes to avoid

Over-cleaning

Don’t remove too much data in pursuit of perfection. Set business-driven quality standards, not technical perfection. Test cleaning rules on samples first, and create “quarantine” processes for questionable data instead of deleting it immediately.

Also, avoid deleting rows just because one column has a NULL value if the other fields still contain useful data. Instead, consider filling in the missing value (imputation) or adding a flag to mark it.

Too much manual work

Automate high-frequency, rule-based tasks. Save manual review for complex cases and business rule exceptions. Document manual interventions so you can find automation opportunities later.

Poor documentation

Record why you made each cleaning rule, document data sources and their specific issues, create visual workflows, and maintain change logs for rule modifications.

Vendor dependence

Understand the logic behind vendor cleaning tools, maintain internal expertise in core techniques, create backup procedures for critical operations, and regularly evaluate alternatives.

The bottom line

Good data cleaning isn’t about perfection – it’s about making your data reliable enough to support better decisions. Start with a systematic approach, measure your results, and keep refining your process based on what your business actually needs.

The key is to automate what you can, document what you do, and focus on the data quality issues that actually impact your business outcomes.

Stop struggling with inconsistent data.

Try Advanced Analytics features.

 

The post Data Cleaning Best Practices: The Foundation for Reliable Reporting Across Teams appeared first on Databox.

However, in situations where you need to quickly pull up a specific KPI or metric, spreadsheets simply won’t cut it. In the sea of raw data, finding the one metric you are interested in can feel like searching for a needle in a haystack, which is where a Google Sheets dashboard becomes essential.

To resolve this issue, we use Google sheets dashboards.  At Databox, we have experts for visualizing dashboards inside or from Google Sheets, as this is one of the main focus points our product solves. Our team ensures that users can seamlessly turn raw data into comprehensive dashboards, providing clear insights at a glance.

Google sheets dashboards are used for storing data in a visual format, which allows you to have a birds-eye overview of your most important metrics.

Dashboards are extremely engaging and they allow your employees, coworkers, and key stakeholders to quickly go over any type of information in a timely manner. 

In this report, we are going to explain exactly what Google sheets dashboards are, how you can create them, and provide you with some templates that you can incorporate into your own company.

• What is a Google Sheets Dashboard?
• Google Sheets Dashboard Tutorial: Create a Comprehensive Google Dashboard in 3 Easy Steps
• How to Build a Dynamic Dashboard In Google Sheets
• Prebuilt Google Sheets Dashboard Templates
• How to Create a Google Sheets Dashboard in Databox
• Google Sheets Dashboard Examples
• Let Databox Build You a Google Sheets Dashboard

Benefits of Using Google Sheets for Dashboards

Google Sheets dashboards offer several key advantages:

• Cost-effective solution compared to other software, as Google Sheets is free
• Ability to display key metrics, KPIs, and important spreadsheet elements in a visually appealing format
• Customizable with various chart types like pie charts, column charts, line charts, and more
• Real-time data updates for interactive and up-to-date reporting
• Integration with the entire Google Workspace ecosystem
• Easy sharing and collaboration features for teams and stakeholders

What is a Google Sheets Dashboard?

Google sheets dashboards are one of the best ways to acquire a clear overview of your company’s key metrics and KPIs since they turn dry data into understandable visuals.

With the use of graphs, charts, and tables, your readers will have an easier time comprehending the important information and use it to make better data-driven decisions.

Plus, if you put a bit more work into the visuals, you can make the dashboard look both beautiful and professional, and impress your audience with a unique aesthetic.

This isn’t really the case with spreadsheets though, as they quickly become an ‘eye sore’ and you won’t be able to extract important data in a timely manner when it matters the most.

Furthermore, a dashboard in Google sheets can focus on different things. There are project dashboards, company-wide dashboards, team-specific dashboards (Marketing, Sales, HR, etc.), executive dashboards, and plenty more.

Nowadays, using a data dashboard has become pretty much standard practice among companies. Team leaders will use them to showcase their performance to an audience by emitting them on an office TV screen.

This results in better-motivated teams, helps keep everyone in the loop, allows high-ranking members to make quick decisions, and makes identifying problematic areas a whole lot easier.

Related: How to Create a KPI Report in Google Sheets? Step-by-Step Guide

Common Challenges When Creating Dashboards in Google Sheets

While Google Sheets offers many benefits for creating dashboards, there are some common challenges to be aware of:

Performance Issues with Large Datasets: Google Sheets can slow down significantly when dealing with large amounts of data, impacting the dashboard’s responsiveness and update speed.
Limited Customization Options: Compared to specialized BI tools, Google Sheets has limitations in terms of advanced customization and design options for dashboards.

Additionally, reviewing numbers alone doesn’t always explain what’s driving changes. When performance shifts, teams still need to dig into historical data and metric definitions to understand the cause. That’s why companies now use AI tools like Databox MCP to ask direct questions about performance in plain English and get answers based on their real business data. Because it applies historical context and understands how metrics are defined internally, it can clearly explain why trends moved up or down, making dashboard reviews more actionable and grounded in context.

Our 3-Step Google Sheets Dashboard Tutorial: How to Create a Dashboard in Google Sheets

Now that you know what a Google sheets basic dashboard is and how important it can be, you are probably feeling tempted to try it out.

If that’s the case, here are the three easy steps you should follow when creating a dashboard in Google sheets.

Let’s dive in and learn how to create your first dashboard in google sheets.

• Step 1: Importing or Gathering Data
• Step 2: Parsing Data (Using Formulas)
• Step 3: Visualizing Data

Step 1: Importing or Gathering Data

The first thing you will have to do is make sure that you have enough raw data in your Google sheet before you start building a dashboard.

There are a few different ways you can import data into your sheet, so let’s go through them one by one.

Using IMPORT Functions

In case the data you want to import is already accessible, you can use Google sheets’ IMPORT functions to get the job done.

Depending on your format, here are some of the most-used functions:

• IMPORTDATA – Used for importing csv and tsv formatted data.
• IMPORTRANGE – Used for importing data within a specific range of cells.
• IMPORTFEED – Used for importing ATOM and RSS feed data
• IMPORTXML – Used for importing several data types (TSV, CSV, XML, HTML, RSS, ATOM, etc.). This function is essentially a combination of IMPORTDATA, IMPORTFEED, and IMPORTHTML.
• IMPORTHTML – Used for importing data that is located on a specific HTML page.

For this method to work, the data you want to import will have to be publicly available beforehand.

Related: 40 Advanced Google Sheets Tips for Marketing Pros

Using Google Forms

Google Forms can be very useful in case you need to import an abundance of data to your spreadsheet. By using the IMPORTRANGE function we mentioned above, you will be able to quickly transfer the data from Google Forms to Google Sheets.

Also, if you use the QUERY function in addition to IMPORTRANGE, you can filter out the most important data before it makes its way onto the dashboard.

In case you don’t have Google Form and are creating a new one, we recommend that you connect it to a spreadsheet so data can be stored separately and you don’t risk losing it.

Using an External Source via an Add On

While this method does have its advantages, it requires quite a bit of technical knowledge in order to be applied.

You can search for API connector add-ons in the Google Workspace Marketplace and import the data to your Google sheet by using the API.

Although, if the developer ever decides to update the add-on, that might disrupt your dashboard’s functionality. This can be a huge setback since you would have to start building it again from scratch.

Related: 13 Ideas on How to Use Google Sheets In Your Business

Step 2: Parsing Data (Using Formulas)

Okay, so now you have all your data gathered in the spreadsheet and it’s time to move on to the next step – organizing it.

The current state of your dashboard is probably a combination of messy numbers and confusing data. Don’t worry, you will be able to transform that into meaningful insights in no time.

While this step might be a bit more complex than the previous one, you don’t need to be an experienced programmer to get the hang of it – you just have to pay attention to how the formulas work.

Here are the functions that you will need:

• AVERAGE – Used for finding the average value of data in a certain column.
• COUNTIF – This function calculates how many times a specific criterion appeared in an individual column.
• COUNTIFS – Works the same as the COUNTIF function, but only counts the data if it fulfilled a specific condition.
• SUM – Used for summing up all the data in a specific column.
• SUMIF – Works the same as SUM, but only sums up the data if it fulfilled a specific condition.
• SUMIFS – Works the same as SUMIF, but there are multiple different conditions.
• SORT – Used for organizing a specific range of data by a descending or ascending order.
• UNIQUE – Used for recognizing unique values in data sets.

Step 3: Visualizing Data

The final step to create a dashboard in Google Sheets is to visualize the data in your Google sheets dashboard.

This involves adding different elements such as sparklines, tables, charts, graphs, etc.

Here are some of the best features to visualize your data and make it aesthetically pleasing for the readers.

Pivot Table

The Pivot Table feature allows you to organize a large spreadsheet by only using the available data. For example, you can organize data through subcategories like name, date, price, or any other helpful identifiers.

You can create a pivot table by following these steps:

• Select the cells that you want to turn into a table, click on ‘Insert’ in the heading bar, and then press ‘Pivot Table’.
• You will see a pop-up window appear. In it, you can choose the exact data range and select whether you want the pivot table to appear in the existing sheet or a new one.
• The new pivot table should now appear. Also, there will be a sidebar through which you can customize the different elements in the table.

Slicer

To organize your spreadsheet, you can use the Slicer feature.

Slicer, as the name suggests, slices your spreadsheet into separate parts so only the crucial data is showcased. It’s a great way to manipulate what your spreadsheet is displaying.

Here are a few steps you can follow to use Slicer:

• Select Data in your heading bar and click ‘Add a Slicer’.
• Choose a specific data range.
• The slicer will come with a sidebar on the right side. You can use the sidebar to alter the parameters and filter the data by condition/value.
• After you finish customizing the parameters, just go back to the original slicer feature. The data should now be ‘sliced’ and separated from the raw data.

Charts

Charts are one of the best visualization features to transform your data into meaningful insights.

Also, charts are great for accurately representing information since you will be able to easily draw out important patterns.

Follow these steps to incorporate charts into your Google spreadsheet:

• Press ‘Insert’ and then click on ‘Chart’ in the main heading bar.
• A blank chart will appear and you will see a sidebar next to it. In the sidebar, you will have different options for customization.
• Select your ‘Data Range’ in the sidebar and use ‘Chart Type’ to choose a type that fits your spreadsheet.
• Lastly, to alter the parameters of the chart, you should go to the ‘Customize’ tab in the editor.

Sparkline

While charts can be immensely useful when presenting important metrics, they aren’t exactly the best fit for spreadsheets. This is because they take up too much space and cover up cells that include crucial information.

For this reason, you might want to choose Sparkline as an alternative.

Sparkline solves the issue since it essentially adds a chart into one individual cell. It is most commonly used for showcasing how the numbers are progressing (seasonal increases/decreases, economic cycles, etc.).

You can either choose a line chart, column chart, bar chart, or win-loss chart.

Adding a Sparkline is pretty simple, all you have to do is type in this formula: =SPARKLINE(data, [options]).

How to Build a Dynamic Dashboard In Google Sheets

Dynamic dashboards are advanced dashboards in which data automatically updates in real-time, as soon as any changes occur.

They are also known as interactive Google sheets dashboards because you can alter and reorganize the reports rather quickly.

In essence, dynamic dashboards are the same as static dashboards, except they have ‘superpowers’. A static dashboard only showcases a fixed set of metrics and data, while dynamic dashboards update them in real-time.

Creating a dynamic dashboard in Google sheets is also a bit more complicated than creating a normal dashboard.

You will have to organize the data differently, learn additional functions, create new data tabs, and use other methods (e.g. Data validation).

Prebuilt Google Sheets Dashboard Templates

If you think that making a dashboard in Google Sheets, especially for your marketing reports or KPI tracking, is going to take away too much of your time, you might be interested in checking out our Google sheets dashboard template.

Templates can be a great starting point since they will already have a set foundation on what your KPI dashboard or general dashboard will look like.

They can be a great alternative if you’re running short on time and can’t afford to create one from scratch.

There are a few great dashboard template options in Google Sheets, and you can find them on the main screen. You can find options on anything from a Google sheets annual budget report to an executive report and similar templates.

To find these templates, simply go to ‘File’ and then click on ‘Make a Copy’.

How to Create a Google Sheets Dashboard in Databox

With project management tools revolutionizing the way in which spreadsheets and dashboards are created, there aren’t many advantages to utilizing Google Sheets anymore.

Limited automation, integration, and not enough comprehensiveness are just some of the issues that users are having with Google sheets.

Databox can be the answer to these issues. 

Aside from having a bunch of new useful features, Databox also makes the process much less time-consuming.

When creating a dashboard in Google sheets, you might end up spending hours getting the hang of the different functions and utilizing the visualization tools. With Databox, this process lasts literally minutes.

Don’t believe us? Check out this three-step guide to see how easy it is.

• Step 1: Connect Google Sheets
• Step 2: Create custom metrics
• Step 3: Add custom metrics to your databoard

Step 1: Connect Google Sheets

Navigate to Databoards, click + New Databoard > Use Wizard, and select the ‘Google Sheets’ source from the list.

Next, choose the specific Sheet you want to pull data from and press Select file. 

Once you have selected your preferred sheet, the data will appear on your screen with each column defined. Now it’s time to begin creating a custom metric.

Step 2: Create custom metrics

Once you connect the raw data from your Google sheets data, it’s time to create a custom metric.

To make the Google sheet integration even better, Databox uses the Metric Builder tool which provides a smooth visualization experience.

It simplifies the visualization process since everything you want to do will only be a few clicks away, and you won’t have to spend time learning query language or how to write lines of code.

Follow the wizard to select the Metric, Dimension (optional), and Date columns.

Then, name your Custom Metric and choose the appropriate Aggregation Function and Data Type.

Save the Custom Metric, making it available in the Datablock Library.

Step 3: Add custom metrics to your databoard

Open the Databoard in the Databox Designer or create a new one.

Then, use the Metric Library to drag and drop desired Datablocks onto your Databoard.

And that’s it!

PRO TIP: Need Help Pulling All of Your Spreadsheet Data in One Place?

Not sure which metrics to track or dashboards to build from your spreadsheet data? Have old reports you want to recreate in Databox? Share your dashboard needs with one of Databox’s product experts and we’ll build you a customized Google Sheets dashboard for free.

Here is an example of what your dashboard can look like (just imagine your data populating here)…

Whether you’ve exported data into a spreadsheet, entered data manually into one, or have a more complex database setup, Databox can be used to create an easy-to-read and easy-to-share visualization of your unique data.

Learn more about our Google Sheets Dashboard setup here, reach out for assistance via email or chat, or get started immediately by following the steps below:

• Step 1: Sign up for a free trail Databox account
• Step 2: Connect your data with Databox
• Step 3: Share your dashboards wishlist with our team via chat
• Step 4: Receive your dashboard in 24 hours

TRY THIS TEMPLATE

Google Sheets Dashboard Examples

In case you are dealing with a handful of important metrics and KPIs, the templates from Google sheets may not be enough to cover everything you need.

If that’s so, you might be interested in checking out these Databox dashboard examples. We can build any of these for you for free.

• Financial Health Dashboard Example
• Sales Overview Dashboard Example
• HR (Employee Performance) Dashboard Example

Financial Health Dashboard Example

The Financial Health Report Example helps you understand your numbers much more clearly, which later results in better financial decisions.

The questions this dashboard can answer are:

• How much is the revenue growth?
• Am I doing well with customer acquisition?
• How much does the customer acquisition cost?
• How much are the general and administrative costs?

Once you know the answers to these, staying on top of your company’s finances will be a piece of cake.

What’s more, the financial metrics, including those from a budget dashboard, can be transferred to a Google spreadsheet where you can then connect data from the other business systems your company incorporates.

Get your Google Sheets dashboard template by contacting us via chat!

Sales Summary Dashboard Example

To keep track and monitor data from your company’s different sectors (marketing, HR, sales, accounting, etc.) or to effectively manage specific projects, you can use a project dashboard or a sales dashboard example.

While you probably already have team leaders in charge of meeting the quotas, you will want to be informed of all the latest changes as soon as they occur.

However, building a dashboard for each individual department is simply too time-consuming.

This is where the comprehensiveness of the summary dashboard comes in handy, you will gain an overview of all the key metrics from each department in one place.

Additionally, by visualizing these dashboard KPIs, you will make the performance metrics much more understandable to the key stakeholders in your company.

Get your Google Sheets dashboard template by contacting us via chat!

SMB Employee Engagement Performance Dashboard Example

No matter how reliable your employees may be, you should still track their progress towards achieving the overall business objectives.

The best way to do this is through the HR dashboard example. 

This comprehensive dashboard provides you with valuable insights into what exactly is going on among the ranks and you can use it to capture all the important employee engagement data in one place.

Not only that, but you can also use it as a place to track employee sentiment and identify the biggest issues that need to be quickly resolved.

Once you acquire all of this data, you and the other team leaders can use it to make better data-based decisions and create finer employee engagement plans for the following period.

Get your Google Sheets dashboard template by contacting us via chat!

Let Databox Build You a Free Google Sheets Dashboard

Building a dashboard in Google sheets might seem easy at first, but once you roll up your sleeves and start the work, it turns out to be a much more grueling process than you anticipated.

You have to pile up a ton of raw data to begin the process, filter out the exact metrics that you want to track, figure out how the various functions and formulas work, and then learn how to visualize the data through charts and graphs.

This can end up taking a huge amount of time, something that busy executives generally lack.

So why go through all this hassle if you don’t have to?

With Databox, you can sit back and enjoy while our team does the heavy lifting.

All you have to do is connect with someone from our team and explain which data you want to include in the dashboard. We’ll do the rest.

We can set up your first dashboard in less than 24 hours and highlight some of the key functions that our customers usually use for performance analysis.

In case you aren’t sure which metrics should be included in the dashboard, don’t worry, we can also help you determine these KPIs based on your company’s overall goals.

Don’t have time to prepare a dashboard for your next meeting? Sign up for our free dashboard setup and leave a lasting impression on your key stakeholders.

FAQ

The post How to Create a Dashboard in Google Sheets in 3 Easy Steps appeared first on Databox.

That’s the strength of Spreadsheets – collating a lot of information in one place.

And while there’s a lot of functionality within a tool like Google Sheets to categorize and manipulate the data, it’s not the best tool to present performance data to others.

That’s why most people who put together Spreadsheets also look for ways to visualize the data inside of it.

This way, it’s more accessible to others, whether that’s members of your own team, your bosses, or even the board of directors.

Here’s how to easily create a bar graph (or other visualizations) using your performance data in Google Sheets.

• How to Create a Bar Graph in Google Sheets
• How to Label a Bar Graph in Google Sheets
• How to Customize a Bar Graph in Google Sheets
• How to Add Error Bars in Google Sheets
• How to Change a Visualization in Google Sheets
• How to Make a Stacked Bar Chart in Google Sheets
• How to Integrate Google Sheets with Databox
• FAQs Related to Creating a Bar Graph In Google Sheets
• Turn your Google Spreadsheets into Powerful Dashboards

How to Create a Bar Graph in Google Sheets

For the full written tutorial on how to make a bar graph in Google Sheets, continue reading.

Prefer a step-by-step video tutorial? View the 4-minute clip right here…

Now, for the written tutorial…You can create a bar graph in Google Sheets in 3 simple steps:

1. Highlight the cells containing the data you’d like to visualize
2. Click the ‘Chart’ icon in the Google Sheets toolbar
3. Customize and/or change the visualization type in the chart editor

First, you’ll want to highlight the specific cells you’re looking to visualize.

In the example below, we are going to highlight revenue from our fictional online book shop from Q1.

So, we’ll highlight cells C2 through C12. Then, we’ll click the chart icon in the toolbar along the top of the menu in Google Sheets.

This will automatically display the data we’ve just highlighted in our spreadsheet in bar graph form.

Related: 40 Advanced Google Sheets Tips for Marketing Pros

How to Label a Bar Graph in Google Sheets

Now that you’ve created a bar graph in Google Sheets, you might want to edit or customize the labels so that the data you’re showing is clear to anyone who views it.

To add or customize labels in your bar graph in Google Sheets, click the 3 dots in the upper right of your bar graph and click “Edit chart.”

In the example chart above, we’d like to add a label that displays the total amount of website traffic and leads generated in May and June. To do so, we’ll need to click each month under “Series”, then “Add Labels”, and then select the specific range from my spreadsheet that we’d like to display as a label.

In this case, we’d select “May” and “June” in order to use the data from those columns as labels in our bar graph.

Next, we’ll do the same thing for “June.”

Now we’ve added labels showing the specific volume of traffic and leads generated in May and June.

Next, if you’d like to customize the look of your labels––type, font, size, color, etc.––select “Customize” from the chart editor and you’ll find all of your options.

How to Customize a Bar Graph in Google Sheets

Google Sheets provides us with a few different bar chart customization options and they’re all available in the ‘Chart Editor’ tab.

To open it, click the three-dotted lines that show up in the top-right corner of the graph.

Next, press ‘Edit Chart’.

The ‘Chart Editor’ should now appear on the right side of the screen where you’ll see the ‘Customize’ option.

Once you click on it, you’ll be able to check out the different bar graph customization and formatting choices.

Let’s go through each one separately:

• Chart style – This option allows you to modify the font style, border color, and bar graph background.
• Chart and axis titles – Customize the chart title, vertical and horizontal axis titles, and an option to add a chart subtitle. Also, you can change everything regarding the font here as well (type, size, color, etc.).

• Series – As the name suggests, this is where you can customize the series (e.g. color of the bar). If you already have a stacked bar chart in place, you can pick a specific series that you want to modify. This option also allows you to upload error bars and data labels.

• Horizontal axis – Allows you to customize the font type, size, and format of the horizontal axis label. Plus, you can set the maximum and minimum chart values (the bar graph uses dataset-based maximum values by default).
• Vertical axis – Allows you to change the font type, size, and format of the vertical axis label. Also, you can change the placement of the axis and reverse them.
• Legend – Customize the legend settings (e.g. font format position). This is mostly for those of you that include multiple series.
• Gridlines – Change the color of major/minor gridlines or turn them off completely.

That’s it!

Learning how to set up a bar graph in Google Sheets is pretty simple, but we recommend playing around with all these options to better understand them.

Related: 13 Ideas on How to Use Google Sheets In Your Business

How to Add Error Bars in Google Sheets in 4 Steps

Error bars are used to visually illustrate expected discrepancies in your dataset.

In this example, I’m going to try to visualize data from my office supplies shopping list.

Here’s how to put error bars in Google Sheets in 4 steps.

1. Highlight and insert the values you’d like to visualize

2. Google Sheets automatically visualizes your data as a pie chart. To change it, click on the chart type drop-down and then select a column.

Here’s what your chart should look like…

3. To add error bars to the above chart, still on the chart editor pane, navigate to customize and click on series

4. Select the error bars option

Depending on the expected difference in value(s), you may choose to increase or decrease the number, in our case we chose 5%.

Your percentage error bars should look like this.

In addition, there are other types of error bars to choose from depending on how uncertain you are about your data.

How to Change a Visualization in Google Sheets

Once you learn how to set up a bar graph in Google Sheets, you’ll probably want to move on to modifying the visualizations.

On the chart editor on the right-hand side of your spreadsheet graph, click the “Chart Type” dropdown menu.

Here, you’ll see all the different options for visualizing the data you’ve highlighted in your spreadsheet.

You can choose Line, Area, Column, Bar, Pie, Scatter, Map, and Other options.

Select the one you like and your data visualization will change within your spreadsheet automatically.

Related: How to Visualize Data: 6 Rules, Tips and Best Practices

How to Make a Stacked Bar Chart in Google Sheets

We’ve already shown you how to create a bar graph in Google Sheets by using only one data set.

But, that’s not your only option – you can also use multiple series and build stacked bar charts.

For instance, let’s assume your dataset looks like the one below and you want to use it to create a stacked bar chart.

Here’s how to make a stacked bar graph in Google Sheets:

1. Choose a dataset and include the headers
2. Press ‘Insert Chart’ in the toolbar
3. Click ‘Setup’ and change the chart type to ‘Stacked Bar Chart’ in the ‘Chart Editor’ panel.

To modify the chart’s title, simply double-click on it and enter the title you want.

This is what your stacked bar graph will look like once you’re finished:

That covers the standard stacked bar graph.

But, Google Sheets allows you to also create a 100% stacked bar chart where all bars have the same size, and each series’ value is displayed in percentages.

Here’s how you can add a 100% stacked bar graph:

• Follow the above-mentioned steps to create a standard stacked bar chart
• Select the added stacked bar chart and press the three dots in the top right corner
• Click on the ‘Edit Chart’ tab
• Click on ‘Setup’
• You’ll see a ‘Stacking’ tab – simply choose 100%.

This is what you’re 100% stacked bar will look like:

Related: How to Build a Dynamic Dashboard in Google Sheets in 6 Easy Steps

How to Integrate Google Sheets with Databox

So what happens when you want to visualize data from multiple spreadsheets in one place?

For example, say you want to visualize top-of-funnel metrics like Sessions, but you also want to include downstream performance KPIs like signups and revenue, too?

In many cases, this data is pulled from different tools and is, therefore, located in several different Google Spreadsheets. This is when things get messy and complicated and make data visualization in a tool like Google Sheets impractical.

Here are a couple of other reasons why Google Sheets isn’t ideal for ongoing performance monitoring:

• You have to pull the data into the spreadsheet and manually keep it updated
• There isn’t an easy way to share graphs without copying and pasting them into slide decks (by the time you do, the data is outdated)

The next challenge is making sure stakeholders understand what the numbers actually mean. A chart shows trends, but it doesn’t always explain the drivers behind those shifts. That’s where an interpretation layer like Databox MCP can add context by analyzing patterns across your connected data sources and surfacing insights directly alongside your visualizations. Instead of manually explaining spikes or dips in performance, you can pair your Google Sheets charts with automated narrative context that clarifies what changed and why.

With Databox’s integration with Google Sheets, you can simply connect your Google spreadsheets to Databox and visualize any of the data you have stored in seconds.

Here’s a quick video on how it works. (Skip ahead if you’d rather view the skimmable directions below.)

If you have Google Sheets connected in Databox, you are familiar with our Google Sheets Metric Builder and all the options it offers. After helping hundreds of customers set up their own Databoards and gathering feedback, our goal to create an even more seamless experience for our users was finally realized with the addition of the Google Sheets Wizard.

Here’s how it works.

If you are an existing user, the first step is to select “Use Wizard” instead of “Start blank” in the Databoards section when creating a new dashboard.

After that, you have the option to select an existing data source or connect a new Google Sheets.
 

Next, choose the specific Sheet you want to pull data from and press Continue. 

Once you have selected your sheet, the data will appear on your screen with each column defined. Once you’ve determined that everything looks correct, press Continue to begin creating a custom metric.

Now it’s time to add some more information to create the custom metric that we want. Begin by selecting a metric value. From there, you will have the option to further segment it by a dimension. Simply select the data you want the value to be shown for.

Finally, we add our finishing touches. Start with naming your metric, then choose the data aggregation option that works best for the values chosen. Don’t forget to select the favorable trend (in other words, your trending preferences) and the number format. After that, all that is left is to add this metric to your dashboard. 

And you’re done! From a spreadsheet with cells full of data to a striking visualization of the very same data that’s as easy to read as it is to report on, whether for a marketing report or any other business purpose. Need more information on how to create a custom metric using the Google Sheet wizard? Check out our detailed help doc. If you need more info about the best ways to format your spreadsheet for Databox syncing, read our guide.

Need help pulling all of your spreadsheet data? Creating Google Sheets custom metrics may be easier than ever now with our Google Sheets Wizard, but if you’re still unsure how to connect your data or format your Google Sheets, our team of experts is here to help.

Getting started with our free Google Sheets Setup Service is as simple as completing this questionnaire. Once submitted, one of our Google Sheets experts will get in touch and help you create powerful visualizations of your data – as soon as in the next 24 hours.

FAQs Related to Creating a Bar Graph in Google Sheets

Where Is the Bar Graph in Google Sheets?

To start creating bar graph, you need to go to Insert > Chart.

Then, in the pop-up chart menu, click the dropdown under ‘Chart Type’ and choose ‘Bar Graph’.

Just make sure you highlight the data you want to convert beforehand.

How to Make a Simple Bar Graph in Google Sheets

The process for making a simple Google graph in spreadsheets is identical to the one we mentioned above.

But there’s an even easier way to do it.

Use Databox’s dashboard setup if you want someone from our team to do it for you – for free!

Or, you can connect your Google Sheets with Databox and build a bar graph in literally a few clicks.

A great thing about this is that you won’t need to spend any time looking for a Google Sheets bar graph templates.

How to Make a Bar Graph In Google Sheets with Multiple Columns?

A graph bar with multiple columns is also referred to as a 100% stacked bar graph.

Here’s a step-by-step guide on how to make a column graph in Google Sheets:

• Follow the above-mentioned steps on how to create a bar graph, but instead of ‘Bar Graph’, choose ‘Stacked Bar Chart’ in the ‘Chart Type’.
• Select the stacked bar chart and go to ‘Edit Chart’.
• Set the 100% option in the ‘Stacking’ tab.

How to Make a Triple Bar Graph in Google Sheets?

First, follow the steps needed to create a standard bar graph in Google Sheets.

Now, we can change the standard bar graph into a triple bar graph by customizing it.  

This is the exact process of how to make a bar chart with triple columns:

• Go to Chart Editor > Customize
• Select ‘Horizontal Axis’
• In the dropdown menu, tick the ‘Show Axis Line’ tab
• Finish up by setting Axis titles

How to Change Bar Width in Google Sheets?

To change the width of your bar graph, go to Chart Editor > Edit Chart.

Next, click on ‘Customize’ and find the ‘Series’ option. This is where you can modify all the different bar series, including the bar width.

Turn your Google Spreadsheets into Powerful Dashboards

Knowing how to create a bar graph in Google Sheets can go a long way in impressing your company’s key stakeholders in the next meeting.

What’s more, it can even be fun playing around with the different chart options!

However, if you’re dealing with dozens of deadlines, barely managing to stay on top of the daily tasks, and have numerous teams to coordinate with – fun isn’t exactly the best description for the process.

Sure, learning the ropes in Google Sheets isn’t the most complicated task in the world, but it will still take up lots of valuable time.

Luckily, there’s a way to create a spectacular Google Sheet dashboard and add much more than just bar graphs in just a few minutes – via Databox.

Databox allows you to skip all the gruesome manual work when making a bar graph.

Simply choose your data source, pick the metrics you want to include, and visualize them in a stunning dashboard with all the key insights in one place.

Or, skip even that and contact our team directly!

We’ll build you a free dashboard as soon as in the next 24 hours — all you have to do is tell us which data you want to visualize.

Sign up for a free trial and turn your Google Sheets into powerful dashboards now.

The post How to Create a Bar Graph in Google Sheets [3 Easy Steps] appeared first on Databox.

Google sheets dashboards provide a clear overview of information and you can quickly check out any specific metrics that you might need at a moment’s notice.

However, with new data constantly piling up, they have to be updated rather often.

This process can easily be avoided by creating dynamic dashboards in Google sheets.

Google sheets dynamic dashboard is a type of dashboard that automatically updates the included data as soon as any real-time changes occur.

This allows you to quickly identify new trends and opportunities, analyze problematic areas, and resolve any issues that occur in a timely manner.

Below, we will provide you with a detailed step-by-step guide that you can follow to build a dynamic dashboard in Google sheets.

• Step 1: Preparing Raw Data
• Step 2: The Essential Google Sheets Functions You Need
• Step 3: Creating a New Tab to Hold Data
• Step 4: Using Google Sheets Functions
• Step 5: Using Data Validation to Make Your Dashboard
• Step 6: Passing Data Validation Values into the Filter Function
• How to Create a Dynamic Google Sheets Dashboard in Databox?
• Create a Dynamic Dashboard for Your Google Sheets Data in Databox

Step 1: Preparing Raw Data

To begin building a dynamic dashboard, you first have to connect the raw data to a Google spreadsheet and start preparing and categorizing it.

After uploading each data source, we recommend that you run a pivot table report to get a better overview of the data. This helps you identify any potential anomalies (incomplete gaps) and get familiar with the data you will be using.

In most cases, the raw data will represent an abundance of information. For example, if you are building an online sales overview report, you will have a lot of data regarding customer activity, such as the location from where they’ve been buying your products, and the channels they have used to buy them. Without organizing it, this information won’t be of much use.

Now, let’s assume that your eCommerce website has five sales channels, including the official website, affiliates, and paid ads.

Naturally, we will have to organize this data accordingly to try and transform it into something a bit more meaningful.

Here are some of the categories that you can use:

• Day and time categories. Create a day-of-sale category (e.g. Monday) and an hour-by-hour category (e.g. 7 pm to 8 pm).
• Timezone category. Assuming that not all of the buyers will come from the same country, we will have to establish the local time in which they decide to purchase a product. This will allow you to make global comparisons.
• Sales channel category. This category will provide you with a clear overview of where each sale in the spreadsheet is coming from.
• Buyer country category. Since you probably won’t be able to fit every single country in the spreadsheet, you can use columns for some of the major ones like the US, the UK, and Canada, and place the smaller countries in a ‘Rest of the World’ column.

Okay, so now we have connected the data from each source, checked if everything is in order through pivot tables, and categorized it.

Time to move on to the next step.

Step 2: The Essential Google Sheets Functions You Need

If you have any sort of experience with Excel, then you are probably already somewhat familiar with the use of Google Sheets functions.

These functions work pretty much the same both in Excel and Google Sheets.

Here are some of the most important ones you’ll need to create a dynamic dashboard:

• VLOOKUP – The vertical lookup function allows you to track a key value in a specific column of a defined range. It’s essentially the best way to search for a unique identifier in your spreadsheet.
• SUM – Used for summing up all the data into one specific column.
• SUMIF – Works the same as SUM, but only if the data fulfills a certain condition.
• AVERAGE – Finds the average value of data in one specific column.
• COUNT – Counts how many cells contain a number.
• Sparkline – You can use this function to create a dynamic graph that showcases the metric’s progress over time.
• ARRAY_CONSTRAIN – This formula provides a subset based on the input range, using the rows and columns that you specify. There are three subfunctions of ARRAY_CONSTRAIN – input_range, num_rows, and num_cols.
• FILTER – As the name suggests, this function allows you to filter out your data sets. For additional precision, you use the subfunctions range, condition1, and condition2.

Once you learn how to use these functions in your Google sheets, you will be able to easily manipulate the data in your dynamic dashboard.

Related: 40 Advanced Google Sheets Tips for Marketing Pros

Step 3: Creating a New Tab to Hold Data

For our next step, we recommend that you create an entirely new tab so that there is a temporary place where your dashboard data can be stored.

You won’t have to do this each time – it’s just easier to understand the process through it.

Step 4: Using Google Sheets Functions

Time to use the Google sheets functions we mentioned earlier.

To start, go to your new tab and organize the column names by using this function:

=array_constrain(‘Data Only’!A1:AE1,1,99)

The ‘Data Only’ refers to the name of your Google sheet, ‘A1:AE1’ presents the first row of data, and ‘1/99’ is the number of rows and columns.

Next, use the FILTER function by selecting a specific cell and setting up the minimum amounts of inputs. You need two inputs – the data location and the filtering item.

This is what it should look like:

=filter(‘Data Only’!A1:AE242,’Data Only’!C1:C242>=date(2022,1,1))

The ARRAY_CONSTRAIN and FILTER functions provide you with the most possibilities when it comes to designing your dynamic dashboard.

To learn your way around them, it’s best to test out different variations and see how they work.

Related: 13 Ideas on How to Use Google Sheets In Your Business

Step 5: Using Data Validation to Make Your Dashboard

If you have gotten this far, then you’ve probably gotten the hang of manipulating your spreadsheet data and using the different functions.

Now, let’s see how you can make your dashboard using the data validation method.

By using data validation, you will acquire a drop-down menu that can be used for selecting a certain parameter (in our case, a sales channel or a specific time).

Once you connect the data to the parameter, it will automatically update and you won’t have to bother with writing any lines of code.

While data validation isn’t the only method you can use, it stands out as the simplest and most powerful.

Firstly, create a new tab once more and pick a name for it (e.g. Dashboard).

Then, proceed with selecting a specific date range. The great thing about data validation is that you can manually select the date range, there won’t be any particular pre-set range that you’ll have to follow.

After you finish setting up the data validation selectors, we can move on to the ‘dynamic’ part of the dashboard.

PRO TIP: Need Help Pulling All of Your Spreadsheet Data in One Place?

Not sure which metrics to track or dashboards to build from your spreadsheet data? Have old reports you want to recreate in Databox? Share your dashboard needs with one of Databox’s product experts and we’ll build you a customized Google Sheets dashboard.

Here is an example of what your dashboard can look like (just imagine your data populating here)…

Whether you’ve exported data into a spreadsheet, entered data manually into one, or have a more complex database setup, Databox can be used to create an easy-to-read and easy-to-share visualization of your unique data.

Learn more about our Google Sheets Dashboard setup here, reach out for assistance via email or chat, or get started immediately by following the steps below:

• Step 1: Sign up for a free trial
• Step 2: Connect your Facebook Ads account with Databox
• Step 3: Complete the questionnaire
• Step 4: Receive your dashboard in 24 hours

Try this template

Step 6: Passing Data Validation Values into the Filter Function

Lastly, to finalize your dynamic dashboard, you should pass the data validation values into the filter function.

The best thing about Google Sheets is that you won’t need to use a macro or pivot tables to do this (unlike in Excel dashboards, for example).

If you return to the filter functions you used in your new tab (Step 3), you can now connect the data validation values in form of filter inputs.

This is what it’s supposed to look like:

=filter(DATASET, DATA:COLUMN 1 (Logical expression) Dashboard Data Validation Field 1, DATA:COLUMN 1 (Logical expression) Dashboard Data Validation Field 2)

By using some simple operators (e.g. <, >, or =), you use input from both the ‘from’ field and the ‘to’ field, essentially filtering the data field twice.

Once you have all the filters set up, you can proceed to the testing process to check whether the data changes in the new tab you created.

If everything is going smoothly, then your dynamic data selection process is over.

Your final stop will be setting up the pies and charts to make your dynamic dashboard aesthetically pleasing. Since this part depends on your creativity and preference, we won’t be explaining it in a separate step.

Even with a fully dynamic dashboard, you still need to interpret what the changes actually mean. Instead of manually digging through multiple tabs to explain why a metric spiked or dropped, teams now use an AI data analyst like Databox MCP to ask questions about their spreadsheet data in plain English. Because MCP understands your metric definitions and historical context, it can explain trends, highlight anomalies, and surface likely drivers behind performance shifts—so your dashboard doesn’t just update automatically, it also becomes easier to act on.

How to Create a Dynamic Google Sheets Dashboard in Databox?

Let’s face it, Google sheets is a bit outdated.

Business tools are rapidly evolving month after month, and with all the new features being released, there is no way for Gsheets to compare anymore.

Aside from the limited automation and consolidation, creating a dynamic Google Sheet dashboard will end up being far too time-consuming. What might take you hours in Google Sheets can easily be done in minutes using an advanced business dashboards tool.

And that’s where Databox comes in.

Here is a three-step guide that explains just how easy creating a dynamic Google sheet dashboard is in Databox.

• Step 1: Connect Google Sheets
• Step 2: Create a custom metric
• Step 3: Drag and drop your custom metric onto a dashboard

Step 1: Connect Google Sheets

Once you open up your Databox web app, go to ‘Databoards’ to create a new dashboard.

You will see a panel on the left side where you can find the ‘Google Sheets’ data source. When you click on it, it will start connecting the Google sheet to Databox. 

Now, find and connect your spreadsheet to visualize data from it.

Step 2: Create a custom metric

After you have finished connecting your Google sheet to Databox, you can proceed to create your first custom metric.

Databox uses the Metric Builder tool to power the Google sheet integration. With the help of Metric Builder, even users that don’t have any type of technical experience can visualize data simply by making a few clicks on the interface.

This makes the process immensely easier since you won’t have to spend time learning some type of query language or even know how to write a single line of code.

You will only be a few clicks away from extracting custom metrics from your spreadsheets.

Add finishing touches to your custom metric — from naming it and choosing the data aggregation option that works best for you, to selecting your trending preferences and the number format.

Step 3: Drag and drop your custom metric onto a dashboard

After that, all that is left is to add this metric to your dashboard. Simply drag it into your dashboard and drop it in any place you deem fit.

That’s it! Easy, right?

Build Performance Dashboard from Your Spreadsheet Data

For the longest time, Google Sheets has been considered to be the epitome of spreadsheet tools.

However, these days are long past us, and dashboard tools have taken over the spreadsheet business.

While it can still be pretty useful for editing and organizing some smaller amounts of data, Google sheets simply don’t cut it anymore when it comes to creating a dynamic dashboard in a timely manner.

Sure, there are built-in formulas, pivot tables, conditional formatting, and a whole bunch of other features, but using them isn’t exactly the easiest task.

From creating new tabs and categorizing data to figuring out how exactly Google sheet functions work, you will end up losing both your time and nerves.

This is why simplifying the process through Databox can be a lifesaver. Or better yet, a timesaver.

By using Databox, you will be able to connect your Google sheet in a matter of seconds and start customizing it through drag-and-drop features, instead of going through the hassle of using complex functions and formulas.

Not only that, but the process of visualizing your key data through graphs and charts will go from ‘hassle’ to ‘fun’.

However, if you don’t have time for that either, don’t worry – you can hire our team to do it.

All you have to do is connect your data and create a dashboard wishlist, and we will take care of the rest.

Want to save up valuable time and still create a killer dynamic dashboard? Sign up here for a free trial.

The post How to Build a Dynamic Dashboard in Google Sheets in 6 Easy Steps appeared first on Databox.

However, if you want to put your data to use, spreadsheets can be cluttered and hard to read. On the other hand, a Google Sheets dashboard will help make your data easier to read and more actionable for your organization. Creating dashboards from your Google Sheets data is simple with Databox. 

How to Build a Sales Dashboard on Google Sheets 

Build an effective sales dashboard in 5 easy steps: 

1. Determine the goal of your dashboard 
2. Determine the metrics you need to include 
3. Set up Google Sheet 
4. Sync Google Sheet with Databox 
5. Build dashboard within Databox 

Step 1: Determine the goal of the dashboard 

Before you begin to compile your data, consider what the goal of your dashboard is. Who is the dashboard intended for? What are the metrics and KPIs they care about or need to know? A cluttered dashboard can be confusing and difficult to read, so a solid understanding of your audience will help keep your dashboard focused. 

When defining your audience, consider:

• What are their goals and objectives?
• How does sales affect their work? 
• Do they need high-level information? Or something more granular?

Step 2: Determine the metrics you need to include 

With the objectives of your audience in mind, select the metrics you’d like to include. Focusing on the most important metrics will ensure your dashboard is effective and easy to read.

If you need to include many metrics or objectives, create a looped dashboard. A looped dashboard allows you to group together relevant dashboards so you can present a comprehensive story with your data—without the cluttered screen. 

Here are some of the most popular metrics for tracking sales performance:

• Total sales revenue 
• Quarterly sales growth 
• Average deal size 
• Lead-to-close ratio
• Meetings booked 

Step 3: Set Up Google Sheet 

Once you know the metrics you want to track, set up your Google Sheet in a way that makes sense for your objectives. Below is an example:

4. Sync Google Sheet with Databox 

Once you have your spreadsheet ready, connecting it to Databox is easy. First, go to the Data Manager in your Databox account. Click the New Connection button in the top right corner of the page, and then select Google Sheets. 

Select the spreadsheet with the sales data you are looking to visualize. Once selected, you can begin creating the metrics you want to track on your dashboard. 

5. Build Your Sales Dashboard 

Create custom metrics

Creating the custom metrics you need is easy with the Google Sheets Wizard tool. To get started, go to the dashboards section of your Databox account. From here click, “New Databoard” in the top right corner, and then select “Use Wizard”. 

From here, select Google Sheets as your data source. You will then select the specific spreadsheet you want to use for your dashboard. The data will populate on your screen like this: 

Verify the data is correct, and then click “Continue”. 

Time to create your first metric! Select the value you’d like to measure. This is the primary numerical value you want to track for your metric: 

For this example, we’re tracking deal size by industry segment. Once you have selected your primary metric, click “Continue”. 

From here you have the option to further segment your metric by adding a Dimension—this could be something like Region, Industry, or in the example above, Segment. Dimensions will allow you to categorize your metrics the way you want them. 

Once you’ve selected your dimension, click “Continue”. You will then be prompted to select the appropriate date range: 

Click “Continue”. You will be able to name your metric and finish any data selections you may have on the next screen: 

Once you’re finished, click “Continue”. 

On this last screen, you can select the way you’d like to visualize your data, and add it to a new or existing databoard. 

Build your dashboard 

Once you have created all the metrics you want to track, add them to your dashboard. The Databox dashboard designer makes it easy to visualize your metrics the way you want. Select a metric, then choose from a variety of visualization options to find what works best for your data. The dashboard designer allows you to create meaningful dashboards that your entire team can understand. 

Features like goals will help you and your team keep track of your progress towards important targets. Dashboards are easy to share with team members through snapshots or custom reports—now available to build directly in Databox! 

Log in to your Databox account to get started. 

Don’t have an account yet? Sign up here for free. 

The post How to Build a Google Sheets Sales Dashboard in 5 Easy Steps appeared first on Databox.

• Properly format your Google Sheets
• Use our new Google Sheet Wizard for easier metrics building

Below, you can view the full episode or keep reading for a fully transcribed version of the episode, complete with relevant screenshots.

So let’s start.

So let’s start with a brand new Google Doc, and Sheet – I will name it Test Sheet one – 

Now, let’s talk about the data table – we have two options: the vertical and the horizontal view. To get the most from your Google Sheet the vertical setup is recommended – it allows you to include all Date Ranges, values, and dimensions in columns, therefore you can create the entire Databoard with an overview and drill-down data with just a few metrics. While the horizontal has its limitations when it comes to adding more data.

That’s all about the view, easy right. And don’t worry if you already have a horizontal sheet you can easily switch it to Vertical – select – copy – paste special, paste transposed.

Now we come to date formats – as you know date formats are very important when it comes to formatting your Google Sheets, but they also play an integral role in extracting and visualizing data with Databox as the Query Builder will only recognize correct formats.

Doing this manually ensures that you will get it right more easily. So,  The Date should be formatted using a Google Sheets format to look like mm/dd/yyyy or dd/mm/yyyy. Either way, the Date needs to include information on the day, month, and year that this Metric value should be pushed to.

Now keep in mind that if you are using specific Date formats in Google Sheets that are not formatted in a way that works with Databox, you can either quickly reformat the entire column by selecting Format > Number > Date, or if it’s important to you to keep a record of the dates formatted as they are, it’s advisable to create an additional column in your Google Sheet for Dates that will be used by Databox.

So let’s reformat these so that they don’t work with Databox. I’ll choose Date time. Then, I’ll create my new column and call it Databox Dates. Type in = and the cell you’d like to transfer, so =A2 here. Then drag the setting across the other cells. You already know the next trick, select the Databox Dates column click Format > Number > Date. There we go. 

Ok, so far so good, how about we try to format the conversion of currency next.

Let’s suppose you have 3 currencies in the Google Sheet and need to get it all into 1 unified currency. In this case, we are going to use the US Dollar, the British Pound, and the Euro. And let’s say we want to report on everything in Euros.

Here’s how we can do it :

Again, I’ll create a new column. I’ll call this one Amount (Euros) and change the other to Amount (Any) since it will hold any kind of currency. To Column E I will add the formula: =GOOGLEFINANCE(“CURRENCY:USDEUR”)

Notice that when I do this, it shows us the exchange rate. To convert the currency, I will just multiply the cell in Column B and add that to my formula. Then I’ll drag the cell settings down. Right now our formula is assuming everything is converting from USD to the Euro, so I’ll just pop into each cell and make sure it’s converting the right currency. If one is already in Euros I can just delete the formula and do =cell, that way we aren’t missing any data in this column.

For the British Pound I’ll use GBR, aka Great British Pound. Alright. Done! Let’s put everything we learned together and input a new row of data.

Let’s say on April 11, 2022 Monise brought in $755 pounds. Now let’s just stretch down our date format in Column D, and then update the currency formula in Column E. Perfect! It adds very little time and will save your team a ton of headaches. Okay, this is ready to go. Let’s get all of this into Databox and build a dashboard!

Time to Build Our Metrics

This is one of my favorite parts of the process. In Databox we offer the Google Sheet Wizard to help you create metrics from Google Sheets more easily so first let’s try to do that from the sheet we have formatted together – 

So first we will connect our GS – the one we created together – here you can see we are just confirming that everything looks right and we see that it is all formatted properly – Yay Us! And now it’s time to move on and create a metric – 

Begin by selecting a metric value. This is basically just a number that you want to track. From there, you will have the option to further segment it by a dimension which I’ll explain a bit more in a second. Then you’ll add finishing touches like naming your metric, trending preferences, etc. Let’s walk through it together.

For our first one, I want to create an Amount (Euros) metric, that way I can track the money coming in. So select the column, and since we aren’t adding any additional dimensions, we’ll skip this part. For the date column, we want to choose Databox Dates since it is formatted correctly. Then I name it. Trending up is the good one.

Click Continue.

And it is that easy.

Let’s add it to our dashboard. I’m just going to drag it directly from the Metrics Library here… If you can see here, nothing is showing up… that’s because, if you remember, we don’t have any data that goes past April 2021. So I’ll choose all time so we can see all of the data, and let’s graph by year to start. Great! What would be really cool now is to be able to see who is bringing in the most money according to our data, so let’s create a new metric to do that.

In this case, we select Amounts (Euro) as the Value again. Now is the time to add a dimension, in other words, a way to slice and dice this data. We want to be able to see how much money is coming in from each team member, so column C, Owner,  would be our Dimension. Again we’ll choose the Databox Dates column.. Now let’s name it – Amount by Owner – and here is our final product. 

Don’t forget you can always choose the preferred visualization before adding it to the dashboard.

Properly formatting your Google Sheets from the get-go will save you time going forward as it will allow you to use Databox to its full potential. 

It takes a bit of time to master all the formatting but once you see how quickly your data blocks populate on your dashboard and verify the accuracy of the data, it is more than worth it.

And remember, if you lack the time to take this on you can always contact our support team and get a free Google Sheets Setup Service to help you start things off. 

If you haven’t already, just create your free Databox account and reach out to our team either via chat or email.

See you next time. 

The post How to Best Format Your Google Sheets for Databox Syncing appeared first on Databox.

When we introduced the Google Sheets integration with Databox a few years back, it quickly became an easy and compelling way to visualize spreadsheet data, allowing quick access to teammates, executives, and clients alike.

Well, we’ve kicked it up a notch this time, and are excited to announce the brand new Google Sheets Wizard—making the creation of Google Sheets metrics possible in just a few quick steps. With all the properties of the Databox Google Sheets Query Builder, on top of an even more friendly user experience, creating metrics for your Google spreadsheets is now easier than ever.

Get to Know the New Databox Google Sheets Wizard

If you have Google Sheets connected in Databox, you are familiar with our Google Sheets Query Builder and all the options it offers. After helping hundreds of customers set up their own Databoards and gathering feedback, our goal to create an even more seamless experience for our users was finally realized with the addition of the Google Sheets Wizard.

Here’s how it works.

If you are an existing user, the first step is to select “Use Wizard” instead of “Start blank” in the Databoards section when creating a new dashboard.

After that, you have the option to select an existing data source or connect a new Google Sheets data source.
 

Next, choose the specific Sheet you want to pull data from and press Continue. 

Once you have selected your sheet, the data will appear on your screen with each column defined. Once you’ve determined that everything looks correct, press Continue to begin creating a custom metric.

Now it’s time to add some more information to create the custom metric that we want. Begin by selecting a metric value. From there, you will have the option to further segment it by a dimension. Simply select the data you want the value to be shown for.

Finally, we add our finishing touches. Start with naming your metric, then choose the data aggregation option that works best for the values chosen. Don’t forget to select the favorable trend (in other words, your trending preferences) and the number format. After that, all that is left is to add this metric to your dashboard. 

And you’re done! From a spreadsheet with cells full of data to a striking visualization of the very same data that’s as easy to read as it is to report on. Need more information on how to create a custom metric using the Google Sheet wizard? Check out our detailed help doc.

Need Help Pulling All of Your Spreadsheet data?

Creating Google Sheets custom metrics may be easier than ever now with our Google Sheets Wizard, but if you’re still unsure how to connect your data or format your Google Sheets, our team of experts is here to help.

Getting started with our free Google Sheets Setup Service is as simple as completing this questionnaire. Once submitted, one of our Google Sheets experts will get in touch and help you create powerful visualizations of your data.

Start Creating Custom Metrics using Google Sheets Wizard in Databox

The Google Sheets Wizard is available with all plans that include our Query Builder functionality. 

If your plan has access to Query Builder, you can log in and start using the Google Sheets Wizard now.

On a free plan? Take the new Google Sheets Wizard for a test drive by requesting a trial of Query Builder.

New to Databox? Create a free account here.

The post Track and Visualize Data from Google Sheets Easily with New Setup Wizard appeared first on Databox.

Every so often, team leaders will forward these KPIs to you so that you can track the overall performance of your business. According to our report on the state of business reporting, almost half of the companies set their goals for 1 to 5 metrics.

Analyzing the data separately for each department is immensely time-consuming, which is why we use Google Sheets to create KPI reports.

Google Sheets dashboards and KPI reports provide you with a comprehensive overview of the most important metrics from each department, all in one place. With these reports, you will have an insight into which parts of your business are doing great and which may be problematic.

Also, by using visualization tools in Google Sheets, you will be able to present the most valuable data to your key shareholders in an understandable way.

As your reporting matures, it’s also useful to go beyond static dashboards and ask direct questions about performance. Instead of manually digging through tabs to explain why a number changed, teams now use AI data analysts, like Databox MCP, to ask questions in plain English and get answers based on their real metrics, definitions, and historical data. Because the responses are grounded in your actual business data and explain what’s driving changes, this approach helps you interpret trends faster and make day-to-day decisions with more confidence.

In this guide, we are going to teach you how to build a great KPI report in Google Sheets that you can use to impress the highest-ranking members in your company.

• What Is a KPI Report in Google Sheets?
• How to Create a KPI Report in Google Sheets
• Limitations of Using Google Sheets for Dashboards
• How to Create a Google Sheets Dashboard in Databox
• Best Practices for Creating a Google Sheets Dashboard
• Google Sheets Report Examples and Common Use Cases
• Build a Google Sheets Dashboard in Databox

What Is a KPI Report in Google Sheets?

KPIs are metrics that provide you with insight into how your company is performing. They are commonly used for determining whether business goals are progressing in the right way.

In most cases, your department leaders will share the most important KPIs in their area to show you how their team is performing.

However, keeping track of all the significant KPIs from each department is extremely hard without the help of certain tools.

This is why many executives create KPI reports in Google Sheets.

Google Sheets provides a relatively easy way for you to visualize technical data. It includes the common spreadsheet calculations and formulas that you can use for reporting and analysis.

A good KPI report can help you and your teams acquire actionable insights into the performance of each part of the company. You will have a clearer overview of your business performances and you will gain an insight into which areas seem to be causing issues.

By tracking the metrics in your KPI report, you can assess the success of your strategies and the overall health of your business. 

How to Create a KPI Report in Google Sheets

Using KPI reports is one of the best ways to gain perspective over the various departments in your business.

By highlighting all the key metrics in a single project dashboard, you will have access to all the significant data that you will need to make informed decisions.

The best thing is – KPI reports can be extremely flexible.

You can either choose to create a KPI report that covers all aspects of your business (marketing, sales, accounting, HR, etc.) or a specific report that only tracks the performance of a particular department.

However, no matter which KPI report you need, you will have to go through the grueling creation process first.

Creating a KPI report can be extremely frustrating, even for those that have years of experience.

But don’t worry, we have prepared a step-by-step guide that will help you go through it with ease.

Follow these few steps to create a comprehensive KPI report:

• Step 1: Create a Database
• Step 2: Develop a Chart
• Step 3: Format the Chart

Step 1: Create a Database

The first thing you need to do is set a data source for your Google sheet database.

This can either be done through a Google Form that you already use for gathering data or a CSV file from your analytics tool.

However, we recommend that you create a database manually since it’s the best way to later automate data generation in your Google Sheet.

As an example, we will create a ‘monthly marketing expenses’ database. Next, we will add a ‘Budget’ column that we will use to track spending trends.

In case you are using a complex tool like Google Analytics to gather data in your campaign performance, you will need to integrate certain GSheet functions to make the analysis process easier.

These are some of the functions you will need:

• Conditional formatting – Use “IF” conditions to format the cells in your Google Sheet
• Vlookup – Vertical data lookup
• Hlookup – Horizontal data lookup
• Pivot table – Useful for isolating and classifying data

Step 2: Develop a Chart

After creating a database, your next step will be to develop a chart.

Do this by selecting all the data in your spreadsheet and clicking ‘Insert’. Next, select ‘Chart’.

The ‘Chart’ editor option allows you to create a pie chart, bar graph, or any other type of line graph that you want to integrate.

Additionally, you can edit graph/chart details such as axis title, chart height, color theme, and many more.

Related: How to Create A Bar Graph (and more) in Google Sheets

Step 3: Format the Chart

Time for the most important step – formatting your chart into an understandable full-overview dashboard.

Once you are finished with the ‘Chart’ editor, select the chart area and move it away from the data table.

Next, click the ‘three dots’ symbol located in the right corner of the chart area.

You will see two options: ‘Publish it’ and ‘Move to own sheet’.

By clicking on ‘Publish’, the Google Sheet will provide you with a link that you can send to other users. In the ‘Permissions’ option, you can also restrict certain users from entering the link.

In case the published chart is running a bit slow, you can edit the data to see how long it will take for the chart area to be updated.

With the ‘Move to own sheet’ option, you can refresh the data much quicker.

Although, you will have to switch between tabs to edit the data and adapt it to the chart.

By following these steps above, you will be able to create a few different charts and then place them in a separate tab.

With this kind of data visualization, you can compare different sets of metrics in one place.

Limitations of Using Google Sheets for Dashboards

While Google Sheets have long been the epitome of project management tools, we can’t say that’s the case nowadays.

Technology is constantly evolving and with new management tools being released every few months, Google Sheets simply isn’t the best and most practical alternative anymore.

Here are just some of the limitations of using Google Sheets for dashboards.

• Limited Automation Ability
• Limited Integration
• Lacks Comprehensiveness

Limited Automation Ability

If you have gone through the creation process, then you have already experienced having to manually input every single piece of information.

This is because Google Sheets has no automation features.

Sure, you can use a Google Apps Script or modify Google Sheets to fasten up the process, but this isn’t really the easier alternative. Simply learning how to do it will take ages.

Once your projects are up and running, updating a Google Sheet dashboard manually will become incredibly tiresome.

Limited Integration

While there are project management tools that support Google Sheet integration or Google spreadsheet implementation, it’s an extremely rare occurrence.

Most of the time, Google Sheets will only be compactable with the Google Workspace.

This may not seem like that big of a deal, but once you need certain data integrated into your project tool, you will see how big of a hassle it actually is.

Lacks of Comprehensiveness

The third limitation of Google Sheets is that it simply lacks some typical day-to-day functions.

Here are some of the things that GSheets can’t cover:

• Time management
• Time tracking
• Communication
• Internal database categorization

All of these functions are important for growing businesses and if you aren’t using powerful project management software, you won’t get very far with Google Sheets.

How to Create a Google Sheets Dashboard in Databox

As we said, with project management tools constantly evolving, Google Sheets simply can’t keep up with the pace with the new features.

With limited automation, integration, and comprehensiveness, creating Google Sheet dashboards will inevitably take up too much of your valuable time.

This is why advanced project management tools such as Databox are considered to be a much better alternative.

With Databox automation features, you will be able to quickly pull out any useful data into your dashboard and then visualize it at a click of a button. This provides you with a comprehensive and understandable overview of your key metrics.

Not only that, with visualized data, you will have an easier time sharing your performances with the rest of the team.

Want to give it a try? Here’s a quick video tutorial of how it works.

For a more in-depth walk-through, as well as specific use cases for getting started with the integration, continue reading below.

• Connect Google Sheets
• Create a Custom Metric
• Drag and Drop Your Metric Onto Your Dashboard

Step 1: Connect Google Sheets

In the Databox web app, navigate to Databoards and create a new Databoard. In the left-hand panel, switch to the ‘Google Sheets’ source.

Step 2: Create a custom metric

Once you connect your spreadsheet, you can create your first custom metric.

The Google Sheets integration is powered by Databox’s Metric Builder tool. Metric Builder provides a user interface (UI) where non-technical users can visualize their data just by making selections in the interface. With it, there is no need to learn a new query language or even write a line of code.

So, anyone on your team can use Metric Builder to extract custom metrics from your spreadsheets in just a few clicks.

Here is a full explanation of each of the form fields that will help you build a custom metric:

Custom Metric Name

You can enter a name for your metric. Alternatively, leave it blank and skip to the next fields. Once you choose a Value from your spreadsheet, we will automatically populate that Value’s row or column header as the custom metric name.

Value (Metric)

The first step is to select a column, row, or cell range that holds the numerical values you want to visualize. Put your cursor in the Value form field, then make a selection directly on the spreadsheet below by highlighting the cells in the spreadsheet with your mouse.

You can also enter a cell range manually by using the ‘A1 notation.’ (If you are unfamiliar with that concept, you can read more about ‘A!’ notation here).

Values must be numerical values, not strings. You can use currencies or other units with numeric values and we will recognize them. In fact, Google Sheets does a good job of automatically formatting the cells, so you shouldn’t need to worry about formatting them inside Databox.

Date (Timestamp)

 The next step is to select a column, row, or cell range with dates (timestamps). Again, when this input is selected in the Databox Metric Builder interface, you can make a selection directly on the spreadsheet below it by highlighting the cells you want to visualize. Values and Dates must have corresponding values, so make sure you select a similar range of cells. Databox accepts any ‘Date’ or ‘Date time’ that is formatted inside Google Sheets.

To ensure that all cells are formatted correctly, you can select them and go under “Format > Number > Date” within your Google Sheet. If you have hours added please select “Date time” format. If your Date cells are formatted as Strings in Google Sheets (not recommended), we will assume your data is the US date if in the format (Month/Day/Year) and if no day is specified (only Month/Year), we will store values on the first of each month.

Dimension (optional)

If you have additional information in your spreadsheet, for example, Country of purchase, Referer information, Browser, Product name, etc., you can reference cells or ranges for Dimensions by using ‘A1′ notation or by selecting it directly on the spreadsheet preview below the Metric Builder form.

Each metric can support up to one Dimension range. To visualize multiple Dimensions, you must create another custom metric.

Number format and Scale 

Read more about Format and Scale settings in Databox in this article.

Data type

This is the last setting that is important for the correct visualization of your data.

The data type describes the data you’re pulling into Databox and depends on the use-case and kind of values. There are three data types that are described right in the interface. You can learn more about Data types in our help documentation. If you are not sure whether you’ve selected the right data type, you can use the live preview as a way to determine whether your data is being summarized correctly.

On the right side of the Metric Builder form, there is a live preview of your data, which also gives you an option to switch between visualization types like line graphs, pie charts, and numbers. We show only the appropriate visualization for the data you’ve selected.

Step 3: Drag and drop your custom metric onto a dashboard

Once the query is saved, your new metric will appear in the left-hand side panel (under this Google Sheets connection) and you can easily drag and drop it right into your dashboard.

Voila, that’s it!

In addition to visualizing data in a Databoard, you can also use your Google Sheets custom metrics in Alerts, Scorecards, and in Data Calculations.

Best Practices for Creating a Google Sheets Dashboard

There is no “right way” to build a Google Sheet dashboard.

However, there are certain best practices that can take you a few steps closer to developing your perfect Google Sheet dashboard.

Here are some that you might find useful.

• Keep it simple
• Use an Appropriate Color Scheme
• Tie All Your Visualizations into One Story
• Enable Data Filtering
• Read Our Help Article Related to Google Sheets
• Troubleshoot by Checking Out the Query Log
• Select a Whole Column or Whole Row, Rather Than Fixed Ranges
• Avoid Discrepancies for Long Time Periods
• Correctly Format Your Dates in Your Spreadsheet
• Check Your Time Zone Settings

Keep it simple

While adding visuals to your dashboard can be fun, you shouldn’t overdo it. Too much visualized data may backfire on you and distract your key shareholders from what’s important.

Pick formats that can represent your data accordingly and use them to highlight the numbers in the dashboard that you think are most important.

Use an Appropriate Color Scheme

Don’t use flashy color schemes. Instead, pick some neutral colors that aren’t too distracting but still do a good job of highlighting your KPIs.

Tie All Your Visualizations into One Story

You should figure out how to connect your charts/graphs in a way that they tell a specific story.

Simply displaying numbers can be confusing and your shareholders will often be short on time to analyze the meaning behind each KPI. If you are able to tell a story with your visualizations, you and your team will have more time to discuss future strategies.

Enable data filtering

Once you create your dashboard, you should be able to filter your data upon KPI variables.

By using filters, you can analyze data from specific sources and filter the dashboard metrics that fit the criterion.

Read Our Help Article Related to Google Sheets

In case you need additional help understanding Google Sheets, you can read our help articles.

We describe all the Metric Builder fields and provide additional examples.

Troubleshoot by Checking Out the Query Log

Sometimes, you may run into certain issues such as missing some pieces of data.

The best way to figure out the problem is by checking out the Query log.

Follow these few steps:

• Go to the Metric Builder page (under ‘Data Manager’)
• Search for your custom (query) metric
• Check the ‘Log’

It happens that users accidentally change the spreadsheet by moving rows and columns. By checking the ‘Log’, you will have a clear picture of what happened.

Select a Whole Column or Whole Row, Rather Than Fixed Ranges

When referring to Values, Dates, or Dimensions, you should select a whole column or whole row, rather than fixed ranges.

That way, once you add new rows and columns, the data will automatically be recognized and your custom queries won’t need to be changed.

Avoid Discrepancies for Long Time Periods

Discrepancies typically occur if you have previously selected the wrong ‘Data Type’ in the Metric Builder main interface.

Read this article to learn more.

Correctly Format Your Dates in Your Spreadsheet

Always make sure you use the ‘Date’ or ‘Date Time’ to correctly format the dates in your spreadsheet.

Similarly, you can use the ‘Numbers’ or ‘Currency’ options to ensure the correctness of your values.

The best way to define the correct format is by selecting the cells in your Google Sheet and opening ‘Format’ > ‘Number’ > ‘…’.

Check Your Time Zone Settings

If you notice data from December is being stored for November, that means there is a problem in the timezone settings.

Before connecting your spreadsheet, you should check the timezone settings in your Google Sheets (under ‘File > Spreadsheet settings… > Time Zone’).

If you are using Databox, then the GSheet time zone should match the one in your Databox account (you can check it under ‘My Profile’).

Google Sheets Report Examples and Common Use Cases

Do you need a place where you can track the most important metrics from your KPI reports?

Databox customizable dashboards can help.

By using our pre-built dashboards, you will be able to integrate all of your most important data from Google Sheets into one comprehensive report. Plus, with only a few clicks, you can visualize the data and make it more understandable to other high-ranking members of your company.

Here are some of our best examples.

• Financial Health Report Example
• Sector Report Example
• HR Report Example
• Sales Report Example
• Monthly Overview Report Example

Financial Health Report Example

Making informed financial decisions comes from understanding your numbers. The Financial Health Report Example helps you with this.

Some of the things you will learn are:

• How well you are doing with customer acquisition
• What is your revenue growth
• What is the cost of customer acquisition
• What are the general and administrative costs

With all of these questions answered, you will have a better insight into your company’s profitability.

All of your key financial data can be compiled into a single Google Sheet where you can also integrate information from the other business systems that your company uses.

Once the Sheet is set up, you can connect it to this comprehensive dashboard and view all of the key metrics in one place.

Sector Report Example

No matter how big or small your business is, keeping track of all the different departments (sales, marketing, accounting, etc.) can be overwhelming.

That is why we use the Sector Report Example.

Although you probably have team leaders whose responsibility is to meet their team goals, as an executive, you want to be kept in the loop of how things are progressing.

However, creating a specific report for each department takes up too much of your valuable time and just isn’t worth it.

By using a comprehensive dashboard such as the Sector Report, you will be able to integrate the most important KPIs from each of your departments in one place.

You will also be able to visualize all of these metrics and make the performance indicators understandable to the high-ranking members in the company.

HR Report Example

The most valuable asset of any business is the people working there.

And even if you have the most reliable employees, you will still want to track their progress in achieving business goals.

You can do this by using the HR Report Example.

This customizable dashboard allows you to collect employee engagement data through which you will gain an insight into what’s going on among the ranks.

The best thing is, you can use it to create KPI dashboards that monitor employee sentiment and high-priority issues.

When you have this information, you can discuss it with your team leaders and create better employee engagement plans for the future.

Sales Report Example

Now let’s see a few examples of how you can build a sales report in Databox from your Google Sheets data.

Let’s take a look at this spreadsheet.

It’s a log of successful purchases for an imaginary online book shop. It includes the date and time (timestamp) of each purchase (column A), product name (B), revenue of each sale in US Dollars currency (C), referer (D), customer name (E), country of residence (F) and email (G).

We can make many custom metrics out of this spreadsheet.

To get the Revenue metric, select column C (the whole column “C:C”) for Values and for timestamps, select the whole column “A:A” for Dates.

For this kind of example, the correct Data Type is the ‘Unprocessed data (event value)’. This Data Type supports cells populated with event values for the specified Date/Timestamp and for longer Date Ranges (i.e. This Month, This Quarter, etc.), with multiple events, data will be aggregated and the total will be displayed for the time period.

The example spreadsheet includes more data than just revenue, of course.

So, let’s also create a new metric with ‘Country’ dimension (column F), to see how my revenue is distributed across different countries. To create the ‘Revenue by Country’ metric, the query would look like the screen grab below, where I chose column “F:F”  as the Dimension value:

In this case, we switched to the ‘Pie’ visualization because I’m interested in the total distribution in 2018 by country.

One custom metric can use only one dimension. But, if you want to view revenue by different dimensions (besides country), create a new query with a different dimension selected and leave the Values as column C and Dates as column A.

Monthly Overview Report Example

Another common use-case for Google Sheets is when a company manually enters key performance indicators (KPIs) into a spreadsheet each month. As an example, take a look at this spreadsheet.

It’s a spreadsheet template with seven KPIs for an imaginary company.

It includes the months (row 1), sessions (row 2), new customers for each month (row 3), a calculated conversion rate (row 4), monthly revenue in US Dollars currency (row 5), average revenue per customer (row 6), expenses in US Dollars (row 7) and profit (row 8).

(As an aside, the conversion rate is calculated inside this Google Sheet. I could have also set up this calculation inside Databox with the use of the Data Calculations feature.)

Let’s make a Databoard from this worksheet…

To get the Expenses metric, let’s select the row 7 (the whole row “7:7”) for Values and months (the first row “1:1”) for Dates.

For Dates, we have entered Months in the spreadsheet, but these are actually the first day of each Month.

For this example, the correct Data Type is the ‘Daily values (processed data)’. This Data Type supports cells populated with daily (or in this case monthly) values for the specified Date/Timestamp.

In Databox, the latest updated value will be displayed (in case you had multiple columns with the same date, but different times.). For longer Date Ranges (i.e. This Year, This Quarter, etc.), data from each day will be aggregated.

In our example, monthly data will be stored in the first of each month. To have more granular data, you could store daily values in your spreadsheet, too.

Build a Google Sheets Dashboard in Databox

Google Sheets are a useful tool for editing, organizing, and later analyzing the most important KPIs in your business.

Similar to other spreadsheets, GSheets also include built-in formulas, pivot tables, and conditional formatting.

But, even with the built-in charts that you can use for visualization, combining the charts into a comprehensive dashboard is pretty much mission impossible.

Having to manually update your GSheet each time you gather enough data is simply not worth the time or the nerves anymore.

Luckily, Databox has your back.

You can integrate your Google Sheets with our custom dashboard software to create a comprehensive report that includes insightful visualizations of your key metrics.

Combining multiple data sources in one place is one of the main advantages of Databox. By connecting data from your Google Sheets, you can create custom dashboards that showcase the most important KPIs from each of your departments.

Telling the story behind your data has never been easier.

Want to create a KPI report but you are short on time? Sign up here.

FAQ

The post How to Create a KPI Report in Google Sheets? Step-by-Step Guide appeared first on Databox.

Then you are at the right place.

Spreadsheets are very useful for organizing data, but when you have too much, Google Sheets can become rather difficult to manage. But this is where pivot tables and our guide come in.

In this guide, we will share a step-by-step process of how one can use the Google Sheets pivot table function for making data organization easier and more effective. After reading this article you should know all the basics of pivot Google Sheets data sets and understand the basic concepts of using the Google Sheets report editor.

So, let’s get started!

• What Are Pivot Tables?
• Benefits of Using Pivot Tables
• How to Make a Pivot Table in Google Sheets
• Pivot Tables: Tips and Tricks
• How to Refresh a Pivot Table in Google Sheets (and Why)
• How to Build a Cloud Pivot Table
• How to Format Pivot Tables in Google Sheets
• Visualize your Google Sheet Data in Databox

What Are Pivot Tables?

A spreadsheet is just a set of columns and rows. When you add in some formulas, it becomes easier for people with data entry skills to understand the numbers inside cells — but when your spreadsheet starts getting large enough that reading through every little calculation gets difficult (especially if they’re all on different pages), pivot tables come into play.

Pivot tables are undoubtedly one of the most useful tools for organizing and interpreting information on spreadsheets. it makes reading through bulky amounts much easier while still providing valuable insights to readers who don’t want or need all those extra numbers clogging up their brain.

While pivot tables help summarize large datasets, the next challenge is interpreting what those summaries actually mean for your business. Instead of manually reviewing multiple tabs and calculations, many teams now use AI data analysts, like Databox MCP, to ask plain-English questions about trends in their spreadsheet data and get answers grounded in their real metrics, definitions, and historical context. This makes it easier to understand why totals shifted, which segments are driving changes, and how those spreadsheet insights connect to overall performance.

Benefits of Using Pivot Tables

Pivot tables are a fantastic way to organize large data sets so you can easily see what’s going on with your numbers. They also provide other benefits including sorting, analyzing, and managing information all at once.

Sorting Data

By using the Google Sheets pivot table function, you can sort your data in whatever order works best for you. This is especially beneficial if you want to pull out specific information by sorting it first and then creating another pivot table based on that criteria. Sorting at its core is simply changing your spreadsheet’s data set so everything shows up correctly without any confusion or misinterpretations. Pivot Google Sheet tables make the task very easy with their efficient layout design which allows quick number-crunching while maintaining readability of results.

Analyzing Data

Pivot tables give you the power to analyze your Google spreadsheets data and see it from a different perspective. These tables provide insights on how data can be used for business, marketing, etc., which makes them an invaluable tool when you are trying to streamline your decision-making process.

Managing Data

Pivot Google spreadsheet tables can easily manage large amounts of data while still allowing the user to understand what they are looking at. The Google Sheets report editor is an easy way to get started with making changes and new reports, so users don’t have to spend hours trying to figure out how pivot Google Spreadsheets works on their own.

Related: How to Use Google Sheets + Databox to Track & Visualize Performance

How to Make a Pivot Table in Google Sheets

You don’t have to be an expert Google Sheets user to make a pivot table. All you need is the Google Sheets report editor and some data that needs organizing. Once you have your data and spreadsheet ready, follow these steps:

• Creating the pivot table
• Using the Pivot Table Editor
• Building the report
• Reading the Pivot Table

Step 1: Creating the pivot table

Start by opening up your Google Sheet file. Then, find the pivot table icon in the top menu bar to activate it. Once you’ve done that, click on “pivot table” and choose which data set you want to use for the Google spreadsheets report editor.

It should be the one where there are different values associated with each row of numbers. If needed, add or remove columns from your Google sheet before continuing forward so everything fits together properly within your spreadsheet’s layout design.

1. Select Data and click on Pivot Table. 

2. Choose between how you want to insert the pivot table (New sheet or existing sheet).

3. So you just created a pivot table, but the table is empty because you haven’t added any columns, rows, or values to it from your data set.

In order to fill this table, you have to use the pivot table editor shown on the right side of the screen.

That’s it!

Step 2: Using the Pivot Table Editor

The Pivot Table Editor helps you to add or remove data to your pivot table with two different options available. You can choose Google’s suggested rows, values, and goals or edit your pivot table manually.

We’ll go through both of these options.

Suggested pivot tables

Google’s built-in AI makes creating your pivot table a breeze!

To use it, you will need to go through the same initial steps when adding your data and values, but instead of adding them one by one – which can take hours if there are many items – Google automatically generates pre-built pivot table suggestions.

Usually, the suggested pivot table objectives are precise. But check everything before you move further.

The other way to create a pivot table is with the Google Sheets Explore tool – a great feature for analyzing data and getting valuable insights from it. 

To use the Google Sheets Explore tool, click the star-shaped icon on the bottom right of the Google Sheet.

You’ll find the Explore window with a few recommendations regarding your data. 

You can click to generate the specific table and visual presentation options of your data in various recommended formats. 

Manual options

The other option is to edit the pivot table manually.

But before diving in, make sure that these are what each option means:

The four different headers will appear at the top of all created pivots – keep an eye out for them so they don’t get lost among other options on the screen.

• Row label – The column headers of your Google spreadsheet data set.
• Column label – What each row in your Google Sheets pivot table represents, or its values. You can add new ones under this category by clicking on any blank area inside of this section. The more rows and columns there are, the more information is available to sort through.
• Values/goals – Where all numbers are placed after being sorted out based on either their value or goal. If not already filled out with preset categories for sorting purposes, select “value” from the dropdown list above it before starting another manual process if needed.
• Filters – You can filter results from your pivot table. For example, you can apply a date filter if you only want to view the projects that you’ve done or delivered in December.

Step 3: Building the report

The next 3 steps will help you to create a readable Google Sheets report.

But first, under the Pivot table editor, select Rows and Values to add the data.

This is how should your pivot table look like now.

On to creating your report:

1. Add rows

Add Rows category within the Pivot table editor.

Select one row for the pivot table to include the data from chosen column into your pivot table. That data will appear as row headings.

2. Add columns

You’ll see the Values data displayed aggregated information for every column. 

3. Add values

Click on Values. You will see the same column headings list.

Select one and the pivot table will summarize that specific column. 

Reading the pivot table

Open any spreadsheet or other document containing a pivot table. The page field sorts data by main categories from the set, making it easy to find what you’re looking for.

Column fields are at the top of the pivot table.

Row fields are located along the left side of the pivot table. These two sets of fields are calculated within the body of the pivot table.

Data items are in the body of the pivot table. Data in the center of the pivot table is the actual calculated data based upon the row, column, and page field headings.

Take a look at grand totals such as “Total” or “Grand Total” rows and columns. This is the result of the summarized or calculated data.

You can also sort data by specific headings by clicking the drop-down arrows beside any column or row heading.

Related: 13 Ideas on How to Use Google Sheets In Your Business

Google Sheet Pivot Tables: Tips and Tricks

We’re not magicians, but we’ll show you some great tips & tricks that can help you save time processing numbers in your Google Sheets Report Editor.

Hopefully, this list of tips and tricks will make your data processing endeavors smooth.

It includes tips on using multiple value fields, changing aggregation types, adding filters, using multiple row fields, and copying pivot tables.

• Multiple value fields
• Changing aggregation types
• Adding filters
• Multiple row fields
• Copying Pivot Tables

Multiple value fields

You can get a clear picture of how sales prices are distributed into different categories by adding more value columns. Click Add in the Values section of the editor and you can create value columns.

Changing aggregation types

You can produce fresh insights by changing the aggregation type of one of the columns, e.g. change the SUM to AVERAGE instead.

You can select desired aggregation options. Click on SUM (or AVERAGE or other selected column) and choose from the menu:

Adding filters

A nice feature of Pivot Tables is that you can create “named sets” which are just like named ranges, making it easy to have filters based on the same set of values. In this example we will show a count of properties for each property type:

We see all 15 properties from the dataset.

If we choose the filtering by Agent, we will see the data from just one of the Agents.

Click on the “Status > Showing all items” and uncheck the items you want to discard.

Keep selected the data that will be used to create the Pivot Table.

Now you see just Jenny’s selected properties.

Multiple row fields

This one can be very helpful when it comes to different sorting reviews.

In the example below, when you add a second-row field, it appears as sub-categories, so that between the two columns in your Pivot Table all the unique combinations of the two fields are shown.

Copying Pivot Tables

There’s a quick trick for copying an existing Pivot Table, rather than starting over.

It also gives you the option of moving your Pivot Tables to a different tab.

Click into the top left corner cell of your Pivot Table and click copy (Cmd + C on a Mac, or Ctrl + C on a PC/Chromebook). This adds the Pivot Table to your clipboard and you can paste it wherever you want in your Sheet (Cmd + V on a Mac, or Ctrl + V on a PC/Chromebook).

1. Find the copy option for your Pivot Table by clicking the top left corner cell of the Pivot Table
2. Select Copy (Cmd + C on a Mac, or Ctrl + C on a PC/Chromebook).
3. Paste it wherever you want in your Sheet (Cmd + V on a Mac, or Ctrl + V on a PC/Chromebook).

*Note: Ensure that there is enough space available wherever you wish to paste a copy of your Pivot Table.

Related: 40 Advanced Google Sheets Tips for Marketing Pros

How to Refresh a Pivot Table in Google Sheets (and Why)

The good news is – You don’t need to manually refresh pivot tables!

But… There are a few cases in which you might need to force a refresh:

Case 1: Your pivot tables have filters

If you have filters in your pivot table, your data won’t be updated when you change the original data values. To fix this problem, you need to remove the filters in your pivot table. Check out how to remove those filters below.

Make changes to the original data set.

Add again the filters within the Pivot table editor (Click the Add button in the Filters category).

Case 2: Adding new rows that are outside the pivot table’s range

The pivot table only takes the data from the original dataset within the pivot table’s range into account. If new rows of data are added outside of that range, they will not affect the pivot table. You can adjust the pivot table range to fit your data by adding blank rows above and below the initial data so it can be extended as needed or within the pivot table editor.

However, if you leave blank rows in your original worksheet, the pivot table will also show blank rows. To avoid this, you can either add a filter to display only the rows with values or edit the range directly to include your new rows.

Case 3: Your original dataset has functions such as TODAY and RANDOM

If you have pivot tables that update automatically, a simple change to the original dataset won’t update the pivot table. One solution is to avoid including functions such as TODAY and RANDOM in your data or by using cloud pivot tables to update the pivot table.

If you have any of the issues mentioned in the original dataset sheet, both methods will automatically update your pivot tables to the desired version.

How to Build a Cloud Pivot Table

Information stored within a database is often too large to work with using a regular spreadsheet. And while Google Sheets does have a five million-cell maximum capacity, a better option to summarize and analyze large amounts of data is to use Cloud Pivots.

Handling large amounts of data with a Cloud database is much easier than a spreadsheet because Cloud databases let you do things like:

• Query information to see information from another place.
• Sort your data based on any factor.
• Filter your data to see only the “important” parts.
• Use mathematical functions to manipulate your data.
• Data analysis often requires users to work with smaller slices of information.

To build a Cloud pivot table, select the underlying data you wish to visualize. 

Example: Using Salesforce – Select the objects and fields. 

You can build the same Cloud Pivot Tables for databases.

• Step 1: Select the table and fields you want to include in the pivot table.
• Step 2: Select the columns and rows you want to include in each of your measures.
• Step 3: Choose a calculation method for each measure. Example: If you want a total for a particular column, select Sum, then select a field from that column to include in your sum.
• Step 4: Set an auto-refresh schedule.

How to Format Pivot Tables in Google Sheets

Everything starts with the “Format” option in the menu bar.

From the drop-down menu navigate to the “Theme”.

It will take you to the “Themes” window and there you need to click on the box with a downward arrow located at the bottom of this window. This is where you need to select the theme that you’d like to be applied on your pivot table.

Takeaway: It doesn’t matter what kind of data Google Sheets has, but if you use the right visual display, it will make it far more evident and easy to interpret.

Related: How to Create A Bar Graph (and more) in Google Sheets

You can also customize the visuals of your pivot table like shown below.

If you are creative enough you can make amazing themes individually.

Visualize your Google Sheet Data in Databox

What if you could take the same data from a Google spreadsheet and instantly visualize it an easy-to-understand dashboard with just a few clicks?

That’s exactly where Databox can help you! It allows you to layer key metrics on top of your spreadsheet or pivot table. This means that instead of looking at rows and rows of spreadsheets, you can bring in actionable performance insights that help you make smarter decisions.

Databox integrates with Google Sheets to make your data easy to navigate, analyze, and pull insights from. Our tool can help you automatically pull data from any spreadsheet, calculate custom metrics, and more. The combination of tools opens up possibilities around real-time or historical reporting, displaying multiple worksheets in one place, and creating dashboards that will help teams visualize their performance.

Try it today – sign up for a free trial now and join 20,000 satisfied growing businesses and agencies using Databox.

The post How to Use Pivot Tables in Google Sheets: Step-By-Step Guide appeared first on Databox.