Product analytics

The pain

Product data lives in the transactional database. Every business question is a ticket to engineering, and there are no reliable retention or usage metrics at hand.

The cost of not acting

Every decision that waits for a report is a slower decision. Your engineering team gets consumed answering data questions instead of building product, and the business decides with less information than it already has.

The solution

A lightweight lakehouse: ingestion to Amazon S3, catalog, transformation and query with Athena/Redshift + QuickSight, with usage models ready for the team to self-serve.

Architecture, in general: transactional database → ingestion to S3 → catalog and transformation → Athena/Redshift → dashboards in QuickSight, with usage models ready for the business.

The result

Expected outcome (indicative, validated with your data before you decide):

• Self-service business metrics in weeks.
• Engineering freed from reporting tasks.
• Retention and usage measured reliably.