Client confidential · Creator media and paid media
A failed migration became a governed BigQuery platform with expanded platform coverage, automated quality monitoring.
Context
A creator media platform specializing in influencer marketing publishes creator content and runs paid media campaigns through creator profiles on behalf of major national brands. Their business depends on granular, accurate performance data across every ad platform, creator, episode, and conversion event.
When the client came to Maven, a prior migration had stalled at roughly 30% completion. The new models did not work, the consultancy had walked away, and legacy connector pipelines could not support newer platforms or custom attribution windows.
Maven audited the failed implementation and found a data architecture crisis that required a complete rebuild. The engagement evolved into a long-term partnership to transform the client’s analytics infrastructure.
Challenge
Years of technical debt went beyond an incomplete migration: 100+ undocumented dbt models, 2–3 day processing delays, 40+ weekly manual hours, no native 1-day view-first attribution, coverage limited to Facebook and Google, and ~85% data accuracy visible in a client-facing Bubble app.
Approach
Each engagement follows the work required to move from fragmented source data to a reporting layer people can use.
Rebuilt the entire data infrastructure in BigQuery using a medallion architecture with four layers: bronze (raw + standardized naming), silver (subject-area models with cross-channel field standards), gold (fact and dimension tables), and presentation (reporting tables that power the Bubble application). Business logic moved into reusable dbt macros with documentation, automated tests, and multi-tenant configuration.
Where off-the-shelf connectors fell short, Maven combined its own connectors with custom Google Cloud integrations. Standard metrics flowed through Maven connectors; custom APIs delivered advanced attribution and conversion requirements.
Expanded platform coverage from Facebook and Google to seven channels, Facebook, Google, TikTok, Pinterest, LinkedIn, Snapchat, and Roku, and added continuous monitoring that compares live values against validation benchmarks with Slack alerts before discrepancies reach stakeholders.
System view
A failed migration required a full warehouse rebuild, broader platform coverage, and monitoring that could protect reporting continuity.
Facebook, Google, TikTok, Pinterest, LinkedIn, Snapchat, and Roku
Standard connectors combined with Google Cloud integrations
Bronze, silver, gold, and presentation layers with reusable business logic
Reporting tables for a client-facing application without interrupting reporting
Deliverables
Maven rebuilt the warehouse with a bronze/silver/gold/presentation architecture, Maven connectors plus custom API integrations, expanded from 2 to 7 ad platforms, and added automated discrepancy monitoring with Slack alerts, without interrupting reporting.
A four-layer BigQuery and dbt architecture with documented models, tests, and multi-tenant configuration.
Custom integrations for advanced attribution, conversion requirements, and newer platforms.
Coverage expanded from Facebook and Google to seven advertising channels.
Continuous comparison against validation benchmarks with Slack alerts before discrepancies reach stakeholders.
Verified outcomes from the case study
The approved case source reports improvements in accuracy, processing time, platform coverage, and weekly operating capacity.
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