Data Science Tech Brief By HackerNoon · 2026-06-23 · 7 min
This story was originally published on HackerNoon at: . 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: . 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.
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