Analyze BigQuery Data in Connected Sheets: Free Written Tutorials

A spreadsheet is often where an analysis becomes useful to the people making a decision. Google’s Analyze BigQuery Data in Connected Sheets explores how to bring BigQuery data into that familiar workspace, then use formulas, charts, and pivot tables to examine it. The course connects everyday spreadsheet operations with a cloud data warehouse rather than treating them as separate skills.

The complete published written sequence is available for free public reading: three guided lab tutorials followed by a challenge task brief. You do not need an account to read these pages or start a hosted lab to see the instructions. This is a written, lab-based tutorial course, not a video lecture course. Running the activities and satisfying Google’s badge requirements are separate from this free study route.

Course at a glance

What you’ll learn

• Follow the steps for creating, importing, editing, and sharing a Google Sheets spreadsheet.
• Explore the BigQuery console, querying public data, and loading a table into a dataset.
• Understand how a Google Sheets spreadsheet connects to a BigQuery dataset.
• Examine formulas, charts, and pivot tables for analyzing connected data.
• Review extracts, calculated columns, and scheduled refreshes.
• Work through a challenge brief combining connection, analysis, visualization, and transformation tasks.

Skills you’ll gain

• Google Sheets fundamentals
• BigQuery workflow literacy
• Connected data analysis
• Charts and pivot tables
• Calculated columns
• Data refresh planning

Follow the four official reading units

The sequence starts with the spreadsheet, introduces the data warehouse, and then brings them together. These links open the complete public written instructions. Hosted execution remains an optional next step with its own access conditions.

1. Get comfortable with Google Sheets

Google Sheets: Getting Started covers opening a sample spreadsheet, importing a file, creating a spreadsheet, and sharing it for collaboration. The introduction also covers updating and customizing a sheet. This foundation matters because the later Connected Sheets activities still rely on understanding the spreadsheet interface and how work is organized within it.

2. Understand the BigQuery side

BigQuery: Qwik Start – Console introduces querying a public dataset, creating a dataset, loading data into a table, previewing it, and querying the custom dataset. Read this unit to connect the terms dataset, table, and query to the workflow shown in the console, rather than seeing BigQuery only as the source behind a spreadsheet connection.

3. Analyze data through Connected Sheets

Connected Sheets: Qwik Start is the core analysis tutorial. It connects a BigQuery dataset to Sheets, then examines formulas, charts, pivot tables, extracts, calculated columns, and refresh scheduling. Its taxi-data examples include questions about tipped trips, payment types, and ride costs. These examples demonstrate the operations; they are not published findings about your own data.

4. Review the combined challenge

Analyze BigQuery data in Connected Sheets: Challenge Lab combines connecting a dataset, counting rows with a formula, building charts, extracting data, and calculating new columns. It provides the tasks you are asked to complete rather than another fully guided solution. Reading it is a useful way to identify which operations you understand and which instructions you need to revisit.

Who will find this useful?

The Beginner classification suits learners building a foundation in spreadsheet-based data analysis. Comfort with basic spreadsheet navigation will help, but this article adds no prerequisite examination or required credential. The tutorials are particularly relevant when you want to understand how a familiar spreadsheet workflow connects with BigQuery.

For an optional study exercise, choose one example question and note its source data, calculation, visual output, and refresh requirement. This costs nothing and gives your reading a clear purpose. It is a personal learning aid, not an assessed submission or proof that a formula has been tested on a real project.

Free reading and practical access

All four published written units, including the final challenge instructions, can be read without payment. Hosted environments can require credits or an eligible account allowance, and independent cloud usage can involve separate charges. No free execution environment is promised. Google’s formal recognition depends on the required practical activities, so reading the series alone does not establish badge completion.

You can browse the WikiFree course catalogue for related learning or open the parent course to review Google’s current enrollment options.

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