InData Quality & BeyondbySumit Mudliar·Oct 24Where to Test Data in an ETL PipelinePart 4 of Data Testing from Scratch: why testing only the final report leaves you hunting for problems, and what to check at each stage…
InTowards Data EngineeringbyDouble Espresso Data·Oct 22From SQL Analyst to Analytics Engineer (Part 3): Data Quality, The Circuit Breaker, and Hosting…How to turn fragile pipelines into fail-safe architectures using dbt generic tests, circuit-breaker DAGs in Microsoft Fabric, and zero-cost…A response icon2A response icon2
InData Quality & BeyondbySumit Mudliar·Oct 105 Essential Data Quality Checks (with SQL Examples)Part 3 of Data Testing from Scratch — five checks, one small table, and the SQL to run them today.
InData Quality & BeyondbySumit Mudliar·Sep 30The Cost of Bad Data: 6 Real-World Data Quality FailuresA lost spacecraft, missing COVID cases, wrong credit scores and $136 million in fines: what bad data really costs, and the simple checks…
InData Quality & BeyondbySumit Mudliar·Sep 28What Is Data Testing? Definition, Examples & Key Differences
Datagaps Inc.·Jul 3How to Generate 500+ Data Quality Rules at Scale Using AI in the Datagaps DataOps SuiteEnterprise data environments rarely consist of a handful of tables. Production data models in organizations like financial services firms…
InUselessAI.inbyShresth Shukla·Jun 29Aggressive Data Quality testing with 500+ Data Quality Rules Generation using DatagapsHow do you generate data quality rules at scale using AI on enterprise datasets?
Datagaps Inc.·Jun 23How Datagaps DataOps Suite Text-to-SQL Helps You Write Data Validation Queries FasterGenerate SQL test queries from natural language prompts with Datagaps DataOps Suite's Text-to-SQL AI for faster, accurate data validation.
InUselessAI.inbyShresth Shukla·Jun 18How Datagaps Text-to-SQL Helps Data Testing Teams Write SQL FasterWriting SQL queries using prompts for data testing within Datagaps!
