Google BigQuery is a fully-managed data warehouse on RESTful web service that enables scalable, cost-effective and fast analysis of big data working in conjunction with Google Cloud Storage. It is a serverless Software as a Service (SaaS) that has built-in machine learning capabilities.
One of the most common use cases for BigQuery in digital analytics is using it as a central data warehouse for all digital analytics data. This can include data from sources like Google Analytics, Ad platforms, CRM, CMS and even offline data.
For transferring data from various sources into BigQuery, a service known as analytics data pipeline is required. One example of such a service is the Reflective Data Analytics Pipeline.
Using data in BigQuery
Since BigQuery acts in many ways similar to a relational database and it supports SQL queries, using it fairly simple for someone that knows SQL and how databases work.
Query data in BigQuery UI
The simplest way to get started working with data stored in BigQuery is by using the UI to run simple (or advanced) queries.
For example, here’s a simple query against the Google Analytics sessions dataset to see the top 10 countries by the number of sessions for a given day.
The BigQuery UI is not meant for production usage but works well for testing out new queries or even running ad-hoc reports.
BI and data visualization platforms
For more common reports, you will likely use some of the BI or data visualization platforms. Most of them have a BigQuery connector available.
Perhaps one of the most popular tools for this use case is Google Data Studio. It has a native connection with BigQuery and, unlike others, also leverages a smart caching layer that can significantly reduce your BigQuery costs.
If you already have a BigQuery account with some data in it, connecting to Google Data Studio is as easy as choosing the correct account, dataset and table.
Besides Google Data Studio, BigQuery also has connectors built for Tableau, Microsoft Power BI, Redash and many others.
Useful links
- BigQuery documentation
- Visualizing BigQuery data using Data Studio
- How to Query and Analyze Google Analytics Data with BigQuery
- Unsampled Hit-Level Google Analytics Data Without 360
- Reflective Data Analytics Pipeline
Last modified: April 30, 2020
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