Think of BigQuery as one store in an entire mall of possibilities. In addition, this hit-based goldmine sits on the cloud-based infrastructure of Google Cloud Platform, an enterprise cloud computing platform with endless applications from hosting to machine learning. Data teams get the tried-and-true Google Analytics data model, with the ability to break it down to the atomic level and build something new with only a little bit of SQL knowledge.

This is a big deal, as this connectivity was previously only available to enterprise accounts. All Google Analytics accounts using the latest property type can now integrate natively with BigQuery. It combines what analysts know and love about Google Analytics with the power and flexibility of a streaming, event-based analytics platform (think tools like Snowplow, Heap, etc.). Importing Google Analytics Data Into BigQueryīigQuery is perhaps the most empowering platform in all of web analytics. BigQuery helps us to combine, calculate, and analyze digital metrics in a new way. Our Analytics team makes extensive use of BigQuery when working with Google Analytics (GA) data. Scaling up to accommodate more storage space is easy and cost-effective, too. They allow data to be accessed in real-time, enabling faster analysis for marketers and analysts.

Cloud data warehouses provide advantages for tackling large data sets when compared to on-premise servers. It's one of the top data warehouses on the market and was ranked a Leader in the category by a Forrester Wave report in 2021.

This post was originally written in May 2017 and was updated in June 2021.īigQuery is the cloud data warehouse component of Google Cloud Platform.

Google tools for data analysis