Looker

Connect Looker to your Google BigQuery data warehouse to analyze and visualize your event and dispatch data with powerful business intelligence tools

Looker Business Intelligence Integration

Looker is a Google Cloud business intelligence and data visualization platform that enables you to analyze and visualize your event, dispatch, and visitor data. Looker connects directly to Google BigQuery, which serves as the underlying data warehouse. To use Looker with your Ours Privacy data, you must first set up the Google BigQuery integration, then connect Looker to your BigQuery tables.

How the Integration Works

Looker does not require a direct integration with Ours Privacy. Instead, it relies on Google BigQuery as the data warehouse layer:

  • BigQuery as Data Warehouse: Your event, dispatch, and visitor data is stored in Google BigQuery (set up via the BigQuery integration)
  • Looker Connection: Looker connects directly to your BigQuery database to read and analyze the data
  • Business Intelligence Layer: Looker provides semantic modeling (LookML), data exploration, and visualization capabilities on top of your BigQuery data
  • Real-time Analysis: Looker queries BigQuery in real-time, enabling interactive dashboards and reports
  • Advanced Features: Looker supports machine learning integration with Vertex AI, query cost estimation, and handling of nested BigQuery tables

More Information

Prerequisites

Before connecting Looker to your Ours Privacy data, you must:

  1. Set up Google BigQuery integration: Complete the Google BigQuery integration setup to ensure your event, dispatch, and visitor data is being deposited into BigQuery
  2. Verify BigQuery tables: Confirm that your BigQuery tables are populated with data from Ours Privacy
  3. Access permissions: Ensure you have appropriate Google Cloud permissions to connect Looker to your BigQuery project

Data Organization

Looker reads data directly from your BigQuery tables. The data structure in BigQuery follows the same organization as described in the Google BigQuery integration documentation:

  • Events: Daily snapshots of all events in your account
  • Dispatches: Daily snapshots of all dispatches in your account
  • Visitors: Incremental updates for visitor records that have been recently updated

Looker can query these tables using both BigQuery Standard SQL and Legacy SQL, providing flexibility in how you structure your data models and queries.

Data Processing Considerations

Events and Dispatches

Events and dispatches in BigQuery are complete daily snapshots. Looker can query these tables directly to analyze historical trends, create time-series visualizations, and build comprehensive reports.

Visitors

Visitor data in BigQuery requires upsert processing (as described in the BigQuery integration documentation). When querying visitor data in Looker, you may need to:

  1. Handle incremental updates: Use Looker's semantic modeling to create views that account for the incremental nature of visitor data
  2. Deduplicate records: Implement logic in your LookML models to handle visitor record updates
  3. Merge data: Create Looker explores that properly merge visitor updates with existing records

For detailed information on handling visitor data upserts in BigQuery, refer to the Google BigQuery integration documentation.

Getting Started

To set up Looker with your Ours Privacy data:

Step 1: Set Up BigQuery Integration

First, complete the Google BigQuery integration setup:

  1. Contact your account manager to enable the BigQuery integration
  2. Configure your S3 bucket or Google Cloud Storage bucket to receive daily data deposits
  3. Set up BigQuery to import data from your cloud storage bucket
  4. Verify that your BigQuery tables are populated with events, dispatches, and visitors data

For detailed instructions, see the Google BigQuery integration guide.

Step 2: Connect Looker to BigQuery

Once your BigQuery tables are set up and populated, connect Looker to your BigQuery database:

For detailed setup instructions, refer to the Looker BigQuery database configuration documentation.

Additional Resources

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