“The dashboard is wrong” hides three problems. Learn how data quality, data reliability, and data observability differ, and which one you are actually facing.
Data Governance: Catalog, Lineage and Data Quality
Data Governance is how you know what data you have, where it came from, who can see it and whether it is right. This post covers the catalog, lineage, access and data quality, with T-SQL checks you can run.
The 5 Vs of Big Data: Volume, Velocity, Variety, Veracity and Value
The 5 Vs of Big Data are volume, velocity, variety, veracity and value. This post walks a grocery chain through each one, so you can ask the same five questions about your own data before you choose a tool.
Cleaning Messy Data With T-SQL
Cleaning messy data With T-SQL means trimming text, parsing dates safely, and preserving rejected source rows for correction and replay.
Data Quality Rules in T-SQL
Data quality rules in T-SQL turn nulls, duplicates, invalid dates, and broken references into visible failures before rows reach reports.