Data quality is not a problem any single role can solve in isolation. The complexity and scale of modern data ecosystems necessitate a collaborative approach, where quality testing serves as a shared infrastructure across all data and analytics roles.
Because the real differentiator in today’s market isn’t just having data. It’s about having it simplified, integrated, trusted, and continually improving. It’s having a data team you can trust. And control.
Embracing a fundamentally different approach that prioritizes influence over enforcement, iteration over perfection, and advocacy over bureaucracy, that empowers you to take control of data quality assessments.
We’re thrilled to share that DataKitchen has once again been named one of the Coolest DataOps & Data Observability Companies for 2025 by CRN!
We introduce a new, more effective approach to data quality assessments, enabled by DataKitchen’s free open-source software
Gartner/Harvard study: “Fire your data team tomorrow” and replace data and analytic teams with “affirmative decision AI agents”
Announcing Actionable, Automated, & Agile Data Quality Scorecards
We want to share our observations about data teams, how they work and think, and their challenges. We’ve identified two distinct types of data teams: process-centric and data-centric. Understanding this framework offers valuable insights into team efficiency, operational excellence, and data quality.
Using the ecological idea of the ‘Tragedy Of The Commons’ as a metaphor for the eternal issue of data quality, we talk about how data quality leaders can leverage Dale Carnegie’s 100-year-old ideas on influencing people and wrapping this improvement process with DataOps iterative improvement.
Now With Actionable, Automatic, Data Quality Dashboards. Learn about DataOps Data Quality TestGen 3.0.
DataOps Data Quality TestGen:
Simple, Fast, Generative Data Quality Testing, Execution, and Scoring.
[Open Source, Enterprise]
DataOps Observability:
Monitor every date 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.
