Most data quality advice tells you what to measure. This book explains why your team keeps failing and what to do about it. https://hubs.ly/Q04bFl4F0 #dataengineering #dataquality #opensource #dataobservability
DataKitchen
Software Development
Cambridge, MA 7,472 followers
DataOps: Open Source Data Quality and Data Observability Software
About us
87% of data projects never make it into production. It’s not because data professionals aren’t working hard or smart. Every company strives to use data to drive their organization forward, but most data projects fall short of expectations. DataKitchen provides software to observe and automate every data journey in an organization, from source to customer value, in development and production, so that teams can deliver insight to their customers with few errors and a high rate of new insight creation. Our software allows data and analytic teams to observe, test, and automate the tools, data, processes, and environments in their entire data analytics organization, providing massive increases in quality, cycle time, and team productivity. Download your free copy of the DataOps Cookbook 3rd Edition to learn about DataOps: bit.ly/DataOpsCookbook2ndEd!
- Website
-
https://datakitchen.io/
External link for DataKitchen
- Industry
- Software Development
- Company size
- 11-50 employees
- Headquarters
- Cambridge, MA
- Type
- Privately Held
- Founded
- 2013
- Specialties
- Agile Data and Analytics, AnalyticOps, DataOps, Data Engineering, ModelOps, MLOps, Data Observability, and Data Quality
Locations
-
Primary
Get directions
1 Broadway
14th Floor
Cambridge, MA 02142, US
Employees at DataKitchen
Updates
-
TestGen Now Supports Oracle and SAP HANA, with a New Setup Wizard to Get You Running Fast https://hubs.ly/Q04bFkGt0 #dataengineering #dataquality #opensource #dataobservability #dataops
-
-
Watch the on-demand webinar: The Four Points In Your Medallion Architecture Where Data Testing Really Matters https://hubs.ly/Q04bFl1K0 #dataengineering #dataquality #opensource #dataobservability #dataops
-
-
Context As Infrastructure: The Six-Category Framework for AI-Ready Data Analysis This layer sits between your data and your AI, transforming schemas into meaning, tables into business concepts, and raw query results into answers your analysts can trust. https://hubs.ly/Q04clwDd0
-
-
DataKitchen Webinar: 10x Your Data Engineering with AI: Patterns That Actually Work Register Now: April 30th, 2026; 12 pm EST / 4 pm GMT https://hubs.ly/Q04bCCxL0 #dataengineering #dataquality #dataops
-
-
Data Production Tripwires in Databricks: Stop Bad Data Before It Reaches Production https://hubs.ly/Q04bFdlx0 #dataengineering #dataquality #opensource #dataobservability #dataops
-
-
♨️ Webinar TODAY: Context Engineering 101 Sign Up Today: April 14th, 2026; 12 pm EST / 4 pm GMT https://hubs.ly/Q04bF9mF0 #dataops #dataengineering #dataquality
-
-
♨️ Webinar: Context Engineering 101 Sign Up Today: April 14th, 2026; 12 pm EST / 4 pm GMT https://hubs.ly/Q04bCKgN0 #dataops #dataengineering #dataquality
-
-
AI does not fail because it is artificial. It fails because it lacks context. If your AI analytics projects keep producing confident nonsense, this webinar is for you. We’ll show how context engineering gives AI what it actually needs to work with enterprise data: trusted data, navigable schema layers, and business context that keeps outputs grounded in reality. In this session, DataKitchen practitioners will walk through the formula DT + DX + CTX = 10x, with real examples from Snowflake and Databricks deployments and practical methods for building context pipelines that stay current as your environment changes. 🎩 Hat huge. Hallucinations tiny. Thanks, context engineering. Free webinar. Real examples. No AI fairy dust. 📅 April 14, 2026, at 12 pm EST / 4 pm GMT Register: https://hubs.ly/Q049Rk_n0 #dataops #dataengineering #dataquality #context
-
-
Data Production Tripwires in Databricks: Stop Bad Data Before It Reaches Production https://hubs.ly/Q049J9xt0 #dataengineering #dataquality #opensource #dataobservability #dataops
-