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Unified Data Platform For Marketing Analytics

An entertainment agency faced fragmented and chaotic data across Social, Search, DSPs, and other third-party platforms.

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Challenge:

  • Each platform (Meta, Google Ads, DV360, etc.) had its own schema, access method, and update schedule.
  • ETL processes were hard to scale, and difficult to monitor.
  • Business units waited days for performance insights due to disconnected tools and manual workflows.
  • Data scientists lacked a centralized workspace to share ad-hoc analyses and notebooks.
  • Ungoverned pipelines made audits and client reporting error-prone.

Approach:

  • Built a modern end-to-end data pipeline using Airflow and AWS-native tools, containerized with Docker for scalability.
  • Created a custom JupyterHub-based Data Science environment, enabling analysts to run, share, and collaborate on models and queries using unified warehouse data.

Outcome:

  • Faster, data-driven campaign optimization.
  • Analysts freed from manual data tasks, focusing on actionable insights.
  • Real-time visibility for marketing leaders.
  • Improved governance, audit readiness, and compliance.

Think my experience aligns with your needs? or got any questions that I can help with? Let’s connect.