Scaling Self-Service Analytics in Regulated Banking With Metadata-Driven Design

This story was originally published on HackerNoon at: https://hackernoon.com/scaling-self-service-analytics-in-regulated-banking-with-metadata-driven-design. Scaling self-serve analytics in regulated banking is hard. Learn how metadata-driven design enforces governance while letting teams explore data safely Check more stories related to data-science at: https://hackernoon.com/c/data-science. You can also check exclusive content about #data-engineering, #bigquery, #gcp, #data-governance, #mlops, #cross-cloud-data-platform, #cloud-data-engineering, #self-service-analytics, and more. This story was written by: @jeevanreddygeeredd. Learn more about this writer by checking @jeevanreddygeeredd's about page, and for more stories, please visit hackernoon.com. Self-service analytics in banking is not primarily a technology challenge. It's a governance challenge. This article explores the design of a metadata-driven analytics platform on GCP that enabled business teams to access trusted financial data without creating new silos. Key lessons include treating lineage as a first-class feature, using semantic layers to enforce consistent business logic, and prioritizing auditability over raw performance in regulated environments.