BigQuery sample dataset for Google Analytics gaming app implementation

Flood-It! is puzzle game available both on the Android and the iOS platforms. The app uses the standard Google Analytics gaming app implementation through Firebase. The flood it dataset available through the firebase-public-project BigQuery project contains a sample of obfuscated BigQuery event export data for 114 days.

Pre-requisite

  • You need access to a Google Cloud project with BigQuery API enabled. Complete the Before you begin section in the BigQuery Quickstart guide to create a new Google Cloud project or to enable the BigQuery API in an existing one.

  • You can use the BigQuery Sandbox mode for free with certain limitations. The Free usage tier should be sufficient to explore this dataset and run the sample queries. You can optionally Enable Billing to go beyond the Free usage tier.

Limitations

This dataset contains obfuscated data that emulates what a real world dataset would look like from an actual Google Analytics implementation. Certain fields will contain placeholder values including <Other>, NULL, and ''. Due to obfuscation, internal consistency of the dataset might be somewhat limited.

Using the dataset

  1. The Cloud Console provides an interface to query tables. You can use the BigQuery UI to access the flood it dataset.

  2. If the Editor tab isn't visible, then click Compose new query.

  3. Copy and paste the following query into the Editor field. This query will show to number of unique events, users, and days in the dataset.

    SELECT
  COUNT(*) AS event_count,
  COUNT(DISTINCT user_pseudo_id) AS user_count,
  COUNT(DISTINCT event_date) AS day_count
FROM `firebase-public-project.analytics_153293282.events_*`

  4. For valid queries, a check mark will appear along with the amount of data that the query will process. This metric helps you determine the cost of running the query.

    BigQuery UI showing query validation and query size

  5. Click Run. The query results page will appear below the query window.

    BigQuery UI showing query results

  6. Try running some sample queries.

Next Steps