Analyze raw data with GA and BigQuery
1. Set up an account with Google BigQuery.
You will need BigQuery to query raw data, connect with other external data sources, export data for visual reports, and store your raw data. You own all data you export to BigQuery. Ownership lets you manage permissions on its datasets and projects using BigQuery’s table-level access controls.
2. Set up an account with an analytics service that can extract data from Google Analytics and any systems and interfaces from which you need to pull data.
Good examples are OWOX BI or Electrik.AI’s Google Analytics Hit Data Extractor. If you don’t have a GA 360 account, you need a data extractor to pull the raw data as it moves to GA. You can also use Google Analytics APIs for export data – however, its limitations make it less than ideal for large companies or long-term use by small companies.
3. Connect BigQuery and your data extractor to your Google Analytics account.
4. Set up a Google Data Studio account and link it to your BigQuery account.
Data Studio will allow you to generate, view, and share the reports you pull data from BigQuery. It lets you combine GA data with data from other sources. You can also integrate data from different GA web properties and get unsampled reports.
5. Prepare your raw data for analysis by opening a blank report on the Data Studio landing page.
You can choose to create different types of reports for other pages, or you can collate them into a single page. If there is a template that fits your needs, you can select from a template rather than open a blank document.
6. Hook into your data source by selecting Create New Data Source on the next screen. Choose BigQuery as your data source.
7. Choose the designated account.
8. Under Property, select the website or application from which you are pulling your data.
9. Select the view you want to analyze and click Connect in the upper corner.
For the rawest data, choose Master View, which collects all the data without filters.