A data warehouse like BigQuery provides a centralised place for all your marketing data. By automating the entire data pipeline process with a service like Fivetran, manual effort is eliminated and the risk of errors is reduced.
Businesses are finding it important to analyse data in near real-time in order to make better decisions. One way to do this is by using BigQuery streaming export to combine GA4 intraday tables with daily tables, which allows for up-to-date insights.
The GA4 BigQuery sample ecommerce dataset allows users to explore and experiment with BigQuery event export data without having to set up a GA4 property or exporting their own data.
Data filtering allows you to exclude data streams and events from your BigQuery exports, helping you to limit the size of your export and export only the events you want. It can also decrease the volume of events exported each day to avoid exceeding the export limit.
The pivot table is a very popular functionality in spreadsheet tools like Microsoft Excel. In this blog post I will show some SQL code examples of pivot tables that were made using the GA4 data export and the pivot() operator in BigQuery.
