BigQuery export filtering is now available in Google Analytics 4!

This is great news because previously, data exportation was only available through an enterprise version of Google Ads, Google Ads 360. Now, however, Google Analytics 4 has stepped their game up and made it easier for marketers to filter which data they want to see, and which data they don’t.

What Is BigQuery?

Essentially, BigQuery is a data storeroom that helps marketers manage and analyze data. There are several built-in features like machine learning, geospatial analysis, and business intelligence, which all come together to report data in a clean, streamlined way.

BigQuery also helps marketers store data. If there’s data that a marketer wants to look at from months or years previously, BigQuery can now help with that. Plus, BigQuery stores its data in a cloud, similar to the cloud offered by Apple, which means your data can be accessed from anywhere, anytime, while remaining secure. 

Furthermore, BigQuery is not just for marketers. Although it may seem like the world revolves around those of us who create copy, ads, etc, BigQuery also helps Data Analysts, Data Administrators, Data Scientists, and Data Developers do their job.

When it comes to Data Analysts, BigQuery does a little bit of everything, including querying data, optimizing query performance, and using tools to analyze and visualize data. For Data Administrators, BigQuery manages costs, secures data by applying it to a dataset, table, column, or row, backup data with table snapshots, and much more. 

Data Scientists benefit from BigQuery as well. Data Scientists can expect BigQuery to aid in the understanding of the user journey, manage access controls, and create models. Data Developers also see an increase in benefits while using BigQuery, as the platform helps batch load data and uses the code sample library. 

BigQuery Export Filtering, Explained

BigQuery filters data on an event-level while exporting information from Google Analytics 4, which helps marketers (and data professionals) better manage the data that gets exported to BigQuery. 

Instead of downloading every single piece of data or painstakingly importing specific data sets, users can select data from a list of existing events that have been previously collected. Better yet, users can manually define which events they want excluded from exports. 

Probably best of all, exporting data to BigQuery’s sandbox is free of charge! Not only will users save money by not having to pay for this data analysis, but this implementation will help ad campaigns become more profitable. 

How Does This Help Marketers?

Marketers (and data professionals!) can now benefit from the BigQuery export function available in Google Analytics 4. This function helps keep data all in one place – no more switching back and forth and opening a million tabs. It’s possible to do everything from Google Ads. 

Plus, by choosing the data that gets exported, it can be even easier to track campaigns and to see what is working and what isn’t. Finally, BigQuery export filtering helps build a more comprehensive look at data through the partnership of marketers, Data Analysts, Data Administrators, Data Scientists, and Data Developers. 

BigQuery export filtering is now available in Google Analytics 4. So far, there haven’t been any anecdotes about how well this performs, but it seems like a great idea so far as it centralizes information and streamlines the data analysis process. Whether it turns out to be a hit or a miss remains to be seen – updates tend to be controversial, but we’ll keep our eyes out regarding whether or not this export filtering is as great as it sounds.