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Overview and Use Cases

Data Warehouse provides direct access to your data via Google BigQuery. This enables custom querying, integration with external tools and advanced analysis beyond what’s available in AnalyticsIQ.

Data Warehouse is designed for teams who need full control over their data pipeline infrastructure.

Use Data Warehouse to:

  • Conduct complex joins and transformations across datasets
  • Integrate with BI tools, machine learning models or internal toolsets
  • Enrich or correlate data with external sources
  • Build custom reporting and KPIs

Use Case Examples​

  • Machine learning data pipelines: Train models for churn prediction, pLTV, player segmentation, or dynamic pricing
  • Cross-title player tracking: Identify users who play multiple games across your organization using shared identifiers
  • Ad and IAP behavior analysis: Explore correlations between specific gameplay events and monetization actions, such as ad views or in-app purchases
  • Device-level ROI analysis: Combine revenue data with estimated CPI figures from attribution sources to assess ROI
  • Cross-source revenue validation: Compare in-game revenue data with external sources (e.g. attribution platforms) to validate accuracy and consistency