This webinar unveils the battle-tested FITT (Functional, Idempotent, Tested, Two-stage) data architecture that eliminates endemic burnout, constant firefighting, and hero-driven development that keeps engineers trapped in operational chaos.
Webinar: Test Coverage: The Software Development Idea That Supercharges Data Quality & Data Engineering
In an exciting webinar, we talk about the importance of having test coverage across all your tables and tools
Webinar: A Guide to the Six Types of Data Quality Dashboards
In an exciting webinar, we discuss the six major types of Data Quality Dashboards
Webinar: A New, More Effective Approach To Data Quality Assessments
We introduce a new, more effective approach to data quality assessments, enabled by DataKitchen’s free open-source software
Webinar: Announcing Actionable, Automated, & Agile Data Quality Scorecards – 2024
Announcing Actionable, Automated, & Agile Data Quality Scorecards
Webinar: Data Quality in a Medallion Architecture – 2024
Would you like help maintaining high-quality data across every layer of your Medallion Architecture?
Webinar: DataOps For Beginners – 2024
If you’ve ever heard (or had) these complaints about speed-to-insight or data reliability, you should watch our webinar, DataOps for Beginners, on demand.
Data Quality Power Moves: Scorecards & Data Checks for Organizational Impact
Webinar: Unlocking the Power of Data Observability and Quality Testing
Webinar Summary: Introducing Open Source Data Observability
Christopher Bergh detailed the company’s release of new open-source tools to enhance DataOps practices by addressing common inefficiencies and errors within data teams. During the webinar, he demonstrated how these tools provide robust data observability and automated testing to improve productivity and reliability across data operations.
Webinar Summary: Agile, DataOps, and Data Team Excellence
Gil Benghiat, co-founder of Data Kitchen, began by explaining the overarching goal of achieving data team excellence, which involves delivering business value quickly and with high quality. He detailed data teams’ everyday challenges, such as balancing speed and quality, and the impact of Agile methodologies borrowed from software development practices.
