Growing businesses means growing data. This leads to businesses using a cloud-based storage solution for their data, such as BigQuery. BigQuery’s data warehouse allows businesses to manage their data all in one place. Furthermore, you can access and analyze terabytes of data in seconds, whenever you need it. Businesses simply have to have a BigQuery account, which is ready to be integrated into your software. With this, it’s no surprise that BigQuery is one of the most popular, highly-rated data warehousing products currently on the market.
BigQuery’s ability to integrate with programs such as Google Sheets means that members of organizations can collaborate on projects within a program whilst using an automatic, live stream of data sourced from BigQuery. Additionally, Google Sheets has fantastic integrated analytical features that allow users to optimize and manage their BigQuery data. This is particularly perfect for projects where organizations need to analyze data frequently for updated results. In this article, we will use the case study of importing data of the current Google search trends into Google Sheets.
Let’s explore in more detail what BigQuery is and a step-by-step on how you can connect BigQuery data to Google Sheets automatically.
What is BigQuery?
As one of Google’s many products, BigQuery is a data warehouse storage system that enterprises can use to store all of their data. Its huge processing power allows BigQuery to carry out rapid SQL queries whenever you need them.
Furthermore, under Google’s infrastructure, your data in BigQuery is constantly secure and accessible. This makes it perfect for project collaborations within organizations.
Why connect BigQuery to Google Sheets?
As part of Google’s products, BigQuery can easily be integrated with Google Sheets. This allows you to experience all of the features and tools Google has to offer. Using Google Sheet’s analytical formatting tools such as pivot tables, charts, and formulas, you can effectively transform your data into visual representations. To learn more about Google Sheets’ analytical tools for data, read our article on How to analyze BigQuery data within Google Sheets.
Connecting BigQuery to Google Sheets allows you to transfer and analyze huge amounts of data whilst maintaining a live connection. This means that your data is always updated.
Using our case study, we’d be able to continually update Google search trends data into our Google Sheets file. Then, we’d use Google Sheets’ analytical tools in order to identify the most popular trends or predict search trends to optimize our business’ marketing.
How to connect BigQuery to Google Sheets
There are two main ways you can connect BigQuery to Google Sheets. Firstly, connecting manually through Google Sheet’s data menu. Secondly, connecting automatically using the Sheetgo app.
Let’s use the case example above and connect Google search trends data from BigQuery to Google Sheets.
Firstly, you can manually connect BigQuery to Google Sheets using Google Sheet’s in-built functionality. Here are the following steps:
- In the navigation menu on Google Sheets, select Data > Data Connector > Connect to BigQuery
- From here, select your desired BigQuery project, dataset and table or view.
- Your dataset will now appear in the Google Sheets file.
Connecting BigQuery to Google Sheets automatically using Sheetgo
Although the above is an effective way to connect your data, Sheetgo offers other features which provide more advantages for businesses.
Here are just some of the benefits of using Sheetgo:
- Unlimited rows of data: The in-built data connector function in Google Sheets limits you to about 16,000 rows of imported data. On the other hand, Sheetgo allows you to import unlimited rows of data, perfect for multiple large projects.
- No need for Google Enterprise account: Google’s BQ integration is only for Google Workspace An Enterprise Plus, Education Plus, Enterprise Standard, or Enterprise Essentials account users. With Sheetgo, you don’t need any of these accounts – simply connect your Sheetgo app to BigQuery and begin!
- Experience spreadsheet behavior: Sheetgo’s functions and features allow users to experience native spreadsheet behavior, unlike static results returned to your sheet by Google’s integration.
- Build on your workflow: Instead of a one-off import, Sheetgo allows businesses to continue to build on their workflows and create multiple connections between their imported BigQuery data to other projects. This multifunctionality is completely unique to Sheetgo.
Go on the Sheetgo web app. In your desired project, click Create workflow. Make sure you label this workflow clearly. Click Connect files.
To select your source data, scroll down to the databases section and select BigQuery.
Click Grant permission to allow Sheetgo to connect with your BigQuery account.
Next, you must select your Bigquery Project, Dataset name, and Table or View. This will determine the data you are using.
Once you are happy with this, press Continue.
It’s time to connect this dataset to Google Sheets. Select Google Sheets as your destination. Clearly name your new file.
When you’re happy with this, press Finish and save.
Your finished Google Sheets file should appear with your desired data.
From here, your data in Google Sheets can be automatically updated via your BigQuery data by scheduling automatic updates using the Sheetgo sidebar menu.
As you can see, Sheetgo is the best option for businesses looking to connect BigQuery to Google Sheets. Not only providing a simple and efficient way to connect your data, Sheetgo also has numerous advantages over the native integration that allows you to build up connections between workflows seamlessly.
Moreover, Sheetgo’s integration not only connects to Google Sheets, but also Excel/CVS files – read more about this here in our article on How to connect BigQuery data to Excel automatically.
For more information, tips, and guides for BigQuery and Sheetgo, check out our other posts below.