As your business grows and generates terabytes of complex data stored in different sources, it becomes necessary to incorporate a data warehouse like BigQuery into your data architecture to migrate data from Google Sheets to BigQuery. Filtering terabytes of data on spreadsheets is a monotonous task that limits what can be achieved in terms of data analysis.
In this article, we will show you in detail how you can move data from Google Sheets to BigQuery.
Methods to Connect Google Sheets to BigQuery
Now that we have laid the foundation on spreadsheets and the importance of incorporating BigQuery into your data architecture, let’s now look at how to import data from Google Sheets to BigQuery. It is assumed that you already have a GCP account. If not, you can create one here. Google offers new users $300 in free credits for one year. You can always use these free credits to familiarize yourself with GCP and access BigQuery.
Method 1: Using Hevo to Move Data from Google Sheets to BigQuery
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By using a fully managed platform like Hevo, you bypass all the complexities mentioned earlier, and you can import Google Sheets to BigQuery in just a few minutes. You can achieve this in 2 simple steps:
- Step 1: Set up Google Sheets as a source by entering the pipeline name and the spreadsheet you want to replicate.
- Step 2: Connect to your BigQuery account and start moving your data from Google Sheets to BigQuery by providing the project ID, dataset ID, data warehouse name, and GCS bucket.
For more details, check out:
- Google Sheets Source Connector
- BigQuery Destinations Connector
The main features of Hevo are:
- Data Transformation: It provides a simple interface to refine, modify, and enrich the data you want to transfer.
- Schema Management: Hevo can automatically detect the schema of incoming data and map it to the destination schema.
- Incremental Data Loading: Hevo allows the transfer of modified data in real-time. This ensures efficient utilization of bandwidth on both sides.
Method 2: Using the BigQuery Connector to Move Data from Google Sheets to BigQuery
You can easily import data from Google Sheets to BigQuery using the BigQuery Data Connector. The steps below illustrate how to proceed:
- Step 1: Log in to your GCP console and access the BigQuery user interface via the hamburger menu.
- Step 2: In BigQuery, select “Create Dataset”.
- Step 3: After creating the dataset, create a BigQuery table that will contain the data from your spreadsheet. To create a BigQuery table from Google Sheets, click on “Create Table” in the “Create Table” tab. In the “Create Table” tab, select “Drive”.
- Step 4: Under the source window, choose Google Drive as the source and fill in the “Select Drive URL” tab with the URL of your Google spreadsheet. You can select either CSV or Sheets as the format. Both formats allow you to select automatic schema detection. You can also specify column names and data types.
- Step 5: Fill in the table name and select “Create Table”. Once your Google Sheets are linked to BigQuery, any changes made to your spreadsheet will automatically appear in BigQuery.
- Step 6: Now that we have data in BigQuery, we can run SQL queries on our data. The image below shows a short query we ran on the data in BigQuery.
Method 3: Using the Sheets Connector to Move Data from Google Sheets to BigQuery
This method allows for directly loading Google spreadsheets into BigQuery, but it is only available for Business, Enterprise, or Education G Suite accounts.
Here are the steps to use the Sheets data connector with a public dataset:
- Step 1: Open or create a Google Sheets spreadsheet.
- Step 2: Click on “Data > Data Connectors > Connect to BigQuery”.
- Step 3: Click on “Connect”, then select a Google Cloud project with billing enabled.
- Step 4: Click on “Public Datasets”. Type “Chicago” in the search box, then select the “Chicago_taxi_trips” dataset. Choose the “taxi_trips” table from this dataset, then click the “Connect” button to complete this step.
You can now use this Google Sheets spreadsheet to create formulas, charts, and pivot tables using the various techniques in Google Sheets.
Managing Access and Sharing Settings
It is important to protect your data on both Sheets and BigQuery, so you can manage who has access to the sheet and BigQuery. To do this, simply create a Google group to serve as an access control group.
By clicking on the share icon on Sheets, you can grant access to your team members to allow them to edit, view, or comment. Any changes made here will also be replicated in BigQuery.
This will serve as a form of access management for your dataset.
Limitations of Using the Sheets Connector to Connect Google Sheets to BigQuery
In this article, we have covered two ways to incorporate BigQuery into Google Sheets so far. Despite the countless advantages of the process, it has certain limitations.
- This process cannot support data volumes exceeding 10,000 rows in a single spreadsheet.
- To use the Sheets connector for BigQuery, you must have a Business, Enterprise, or Education G Suite account. This is an expensive option.
Introduction to Google Sheets
Spreadsheets are electronic worksheets that contain rows and columns where users can input, manage, and perform mathematical operations on their data. They provide users with the unique ability to create tables, charts, and graphs for data analysis.
Google Sheets is a spreadsheet program offered by Google as part of its suite of Google Docs editors. This suite also includes Google Drawings, Google Slides, Google Forms, Google Docs, Google Keep, and Google Sites.
Google Sheets offers you the ability to choose from a wide variety of pre-made schedules, budgets, and other spreadsheets designed to enhance your work and make your life easier.
Here are some key features of Google Sheets:
- In Google Sheets, all your changes are automatically saved as you type. You can use revision history to see previous versions of the same spreadsheet, sorted by the people who made the changes and the date.
- It also allows you to get instant insights with its Explore panel. It provides you with an overview of the data from a selection of pre-filled charts and informative summaries to choose from.
- Google Sheets allows everyone to work together on the same spreadsheet at the same time.
- You can create, access, and edit your spreadsheets wherever you are, on your tablet, phone, or computer.
Introduction to BigQuery
Google’s BigQuery is a data warehouse technology designed to make data analysis more productive by providing fast SQL queries for large data sets. The following points highlight how BigQuery can help improve your overall data architecture:
- When it comes to Google’s BigQuery, size is never an issue. You can analyze up to 1 TB of data and store up to 10 GB for free every month.
- BigQuery allows you to focus on analysis while completely abstracting away all forms of infrastructure, so you can focus on what matters.
- Incorporating BigQuery into your architecture opens up Google Cloud Platform (GCP) services. GCP offers a suite of cloud services such as data storage, data analysis, and machine learning.
- With BigQuery in your architecture, you can apply machine learning to your data using BigQuery ML.
- If you and your team collaborate on Google spreadsheets, you can use Google Data Studio to create interactive dashboards and visualizations to better represent the data. These dashboards are updated as data is updated on the spreadsheet.
- BigQuery offers a robust security framework to all its users. It offers a 99.9% service level agreement and strictly adheres to the principles of the Privacy Shield. GCP offers users identity and access management (IAM) where you, as the primary user, can decide which specific data each team member can access.
- BigQuery offers an elastic warehouse model that automatically scales to the size of your data and the complexity of the query.
Conclusion
This blog discusses three different methods you can use to seamlessly move data from Google Sheets to BigQuery.
Visit our website to explore Hevo and try our hassle-free data integration platform here.
In addition to Google Sheets, Hevo can move data from a variety of free and paid data sources (databases, cloud applications, SDKs, etc.). Hevo ensures that your data is constantly and securely transferred from any source to BigQuery in real-time.
Before creating custom processes to move data from Google Sheets to BigQuery, sign up for a free 14-day trial to experience Hevo’s hassle-free data integration platform.
