Public-safe case study · DataBeat
A structured approach to investigating reporting differences across GA4, Google Ad Manager, Parse.ly, and BigQuery.
My role
Data Analyst
Scope
Data quality and reporting
Status
Ongoing practice
Challenge
Digital analytics platforms measure data at different times and through different definitions. When stakeholders need trusted reporting, those differences must be investigated, documented, and resolved where appropriate.
Approach
Confirm the reporting period, metric definition, filters, and expected source of truth.
Use SQL and platform-level checks to trace data from source systems through BigQuery datasets and reports.
Apply QA checks and automation where useful, then communicate the reason for the difference clearly.
Outcome
This work helps maintain trusted reporting across the analytics stack by turning unexplained differences into testable data-quality questions. Client data, internal schemas, and results are intentionally not published.