A check in the wrong place catches bad data too late. See where data quality checks belong: ingestion, transformation, release gates, and quarantine.
“Clean Data” Is Not a Requirement: Writing Rules People Can Act On
Clean is a feeling, not a spec. Write data quality rules with a testable check, a threshold, and a named owner, so every failure is obvious and owned.
Count Is Not Risk: Ranking Data Issues by What They Actually Cost
The biggest pile of errors is rarely your biggest problem. Rank data quality risk by impact and likelihood, not row count, and fix what actually hurts.
Data Quality, Data Reliability, and Data Observability: Telling the Three Apart
“The dashboard is wrong” hides three problems. Learn how data quality, data reliability, and data observability differ, and which one you are actually facing.
SQL SERVER – Implementing Row-Level Security (RLS)
Row-Level Security (RLS) in SQL Server enables fine-grained control over data access, ensuring users can only view or modify rows pertinent to their roles or responsibilities.
SQL SERVER – Dynamic Data Masking (DDM) Introduction
Dynamic Data Masking (DDM) in SQL Server is a feature that helps protect sensitive data by masking it from unauthorized users.
SQL Server Ledger – Are You Really Using This Feature?
SQL Server Ledger – has taken data integrity to the next level, integrating blockchain-style data verification directly into the database.