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When it comes to collecting, storing, and sharing data, Google Sheets is a great option. Its integration with other Google products, like Forms, Drive, Analytics, and BigQuery, make it even more versatile. Free, flexible, and we’ll-connected, tons of data moves through Sheets every day.

However, many are unaware of the possibilities for data analysis in Sheets. In its beginnings, it may have been weaker than other spreadsheet programs, but Sheets has come a long way in a short time.

In this article, you will learn about the features of Google Sheets that make it a great choice for analyzing your data. You will also learn about the different data analysis features available in Sheets, including tools, functions, charts, add-ons, and scripts.

Benefits of Data Analysis in Google Sheets

In addition to the features directly related to data analysis, Sheets has many other features that make it an excellent choice.

  • Access: You have control of access to your data through sharing permissions, which can be applied to entire folders, sheets, tabs, or even cell ranges.
  • Collaboration: Everything is saved automatically, so your team is always working with the same version of your file. In addition to leaving comments and assigning tasks, you can also chat with your team directly.
  • Automation: There are various ways to automate routine tasks in Sheets. In addition to creating macros, the Google Script add-on allows you to script more complex tasks.

To learn more about automating tasks using Macros, check out our related article on Google Sheets Macros: Enable, Create & Use Them. In the next section, you will learn about the tools, functions, and add-ins that you can use to analyze your data in Google Sheets.

How To Perform What If Analysis in Google Sheets
How To Perform What-If Analysis in Google Sheets

The What-If Analysis is a very important concept in financial modeling. Here’s how to perform a What-If Analysis in Google Sheets.

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Data Analysis Tools in Google Sheets

Regardless of the type of analysis you need to do, Sheets has multiple built-in tools and features that can help you. From tools that help you gain insight while exploring your data to add-ons that allow you to program advanced analytical methods, learn how to analyze your data with Google Sheets to make the most of it.

Prepare your data

If your data is stored within Sheets, functions like VLOOKUP and IMPORTRANGE can help you bring your data together. However, Sheets also has a wide array of functions that allow you to import or link to data not stored within the spreadsheet. like IMPORTDATA or IMPORTHTML. You can now also connect directly to BigQuery, and there are add-ons to connect to multiple sources of data, like Google Analytics or Salesforce.

Sheets offers some built-in functions that can be used to clean any dataset, such as “Remove duplicates” or “Trim spaces”. However, it also offers more specific functions for different data types. These include many functions that can be used to clean up text, as well as many others that can help you convert data types, find errors, blank cells, etc.

Linear Regression in Google Sheets (+ Examples)

Linear regression allows us to find a trend in our data, which is useful for forecasts and more. Here’s how to perform a linear regression in Google Sheets.

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Linear Regression in Google Sheets Examples

Explore your data

Once your data is in Sheets and you’ve cleaned it up for analysis, it’s time to go exploring. Sheets has multiple tools that can help you get a feel for your data, including AI insights through Explore. Based on the type of data in your spreadsheet - or on the data you have selected - Explore can provide insights and suggest functions and charts that might help you visualize your data.

Functions that are used universally to explore data - like sorting, filtering, and conditional formatting - can be customized to fit your needs. When working collaboratively, Filter Views are extremely effective when you need to explore your data without affecting other users. Pívot tables are another great way to explore your data, allowing you to quickly view your data from very different perspectives by focusing on what you want. To learn more, check out our article on How to Create and Use a Pivot Table in Google Sheets.

Sparklines and Quick Sums can help by quickly summarizing row or column data using common graphs and calculations. There are also many charts available, so you can visualize different types of data in multiple ways.

Use Functions and Add-ons for Complex Techniques

For more complex calculations and analytical techniques, you can choose from a variety of built-in functions, like LINEST, which performs the required calculations needed to carry out simple and multiple linear regression analyses directly in Sheets.

Sheets has almost 500 functions that you can use directly from a cell, in many different categories, like Text, Database, Lookup, Filter, Logical, Math, Statistical, Financial, etc. However, if you can’t find what you’re looking for within the built-in functions, add-ons can help you expand your data analysis toolkit. Goal Seek, for example, is a free add-on that allows you to carry out different types of what-if analyses in Sheets.

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Conclusion

As you have seen, in addition to robust collaboration and automation features, the possibilities for data analysis are comprehensive and more functionality is added with each upgrade. From data collection to final analysis, you can do it all from Sheets.

If you want smarter automation and data management, a tool like Layer will allow you to take your data to the next level without having to sacrifice Sheets’ functionality.

You now know how to analyze your data using the tools and functions provided by Google Sheets, as well as by using some of the data analysis add-ons available in the Workspace Marketplace. To learn more about data analysis techniques in Google Sheets, check out our articles on Linear Regression in Google Sheets and How To Perform What-If Analysis in Google Sheets.

Hady ElHady
Hady is Content Lead at Layer.

Hady has a passion for tech, marketing, and spreadsheets. Besides his Computer Science degree, he has vast experience in developing, launching, and scaling content marketing processes at SaaS startups.

Originally published Sep 5 2022, Updated Mar 22 2023