Data profiling has re-emerged as an essential first step in protecting AI-driven organizations from data-induced failures. Most open-source profiling tools stop at describing data; almost none automatically convert profiling insights into actionable data hygiene checks.
With 50+ vendors to choose from, data quality and data observability software has never been more powerful, more plentiful, or more confusing—until now.
Welcome to Analysis-A-Palooza: The Festival No Data Engineer Asked For
AI is changing the world — in this webinar we show how Large Language Model drive the need for DataOps, Data Quality, and Data Observability
When data team leaders hear “data products,” they immediately think of the stuff their team creates. But focusing on the “what” completely misses the mark. Data products aren’t about what you create, but “how” you build, maintain, and continually improve your data deliverables to your customers.
We explore the new generation of open source data quality software that uses AI to police AI, automate test generation at scale, and provides the transparency and control—all while keeping your CFO happy.
DataOps TestGen Enterprise is now compatible with Google BigQuery and can be used to profile and test file-based data accessible through Redshift Spectrum and Snowflake external tables using Apache Iceberg and other file formats.
The manufacturing industry learned decades ago that catching defects early in the production process saves exponentially more money than fixing them after products ship. Today’s data engineering teams face a strikingly similar challenge.
For data engineering teams serious about delivering production-grade data products, implementing systematic test coverage across their Medallion architecture represents not only a technical improvement but a fundamental shift toward sustainable and trustworthy data operations.
💥 80% of data governance initiatives fail. Not because of tools. Not because of frameworks. But because the business isn’t involved, and no one agrees on what data truly matters. That’s where Critical Data Elements (CDEs) change everything.
The 2026 Open Source Data Profiling Software Landscape
DataOps Data Quality TestGen:
Simple, Fast, Generative Data Quality Testing, Execution, and Scoring.
[Open Source, Enterprise]
DataOps Observability:
Monitor every data pipeline, from source to customer value, & find problems fast
[Open Source, Enterprise]
DataOps Automation:
Orchestrate and automate your data toolchain with few errors and a high rate of change.
[Enterprise]
DataOps Consulting, Coaching, and Transformation
Commercial Data & Analytics Platform for Pharma
Data Production Teams
Data Science/AI
Data Engineering
Data Quality
Business Analytics
Data Products
Data Mesh
Data Contracts
ModelOps / MLOps
DataGovOps
Self-Service Operations
Data Quality Assessments
Data Quality Testing
Data Observability
Data Orchestration
Monitor every Data Journey in an enterprise, from source to customer value, in development and production.
Simple, Fast Data Quality Test Generation and Execution. Your Data Journey starts with verifying that you can trust your data.
Orchestrate and automate your data toolchain to deliver insight with few errors and a high rate of change.