Blog
Why We Open-Sourced Our Data Observability Products
Why open source DataOps Observability and DataOps TestGen? Our decision to share full-featured versions of these products stems from DataKitchen’s long-standing commitment to enhancing productivity for data teams and promoting the use of automated, observed, and trusted tools. It aligns with our company’s philosophy of sharing knowledge and now software to inspire teams to implement DataOps effectively.
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.
Congratulations to the Karuna Team for their acquisition!
Today, Bristol Myers Squib (BMS) has fully acquired Karuna Therapeutics. We congratulate our customer on their fantastic success.  Their product, KarXT, an antipsychotic, is revolutionary and is lined up for an FDA Prescription Drug User Fee Act (PDUFA) in September...
Embracing Agility and Excellence in Data Operations: The DataKitchen DataOps Way
Embracing Agility and Excellence in Data Operations: The DataKitchen DataOps Way When the founders of DataKitchen met, it was at a company that offered a managed service for healthcare insights and data. Initially, their customer found data errors, the team...
Key Success Metrics, Benefits, and Results for Data Observability Using DataKitchen Software
Key Success Metrics, Benefits, and Results for Data Observability Using DataKitchen Software Lowering Serious Production Errors Key Benefit Errors in production can come from many sources – poor data, problems in the production process, being late, or...
ngx-toolkit, a new open-source project from DataKitchen
ngx-toolkit, a new open-source project from DataKitchen At DataKitchen, we use Angular and strive for well-tested and maintainable code. We’ve created three libraries that have helped accelerate Angular development in our software projects. We are proud today to...
Why Not Hearing About Data Errors Should Worry Your Data Team
Why Not Hearing About Data Errors Should Worry Your Data Team In the chaotic lives of data & analytics teams, a day without hearing of any data-related errors is a blessing. Your team is on top of things, deliveries are on schedule (you think), and no major...
Your LLM Needs a Data Journey: A Comprehensive Generative AI Guide for Data Engineers
Your LLM Needs a Data Journey: A Comprehensive Guide for Data Engineers The rise of Large Language Models (LLMs) such as GPT-4 marks a transformative era in artificial intelligence, heralding new possibilities and challenges in equal measure. LLMs have the potential...
DataKitchen Resource Guide To Data Journeys & Data Observability & DataOps
DataKitchen Resource Guide To Data Journeys & Data Observability & DataOps Data (and Analytic) Observability & Data Journey – Ideas and Background Data Journey Manifesto and Why the Data Journey Manifesto? Five Pillars of Data Journeys Data Journey First...
The Art of Data Buck-Passing 101: Mastering the Blame Game in Data and Analytic Teams
The Art of Data Buck-Passing 101: Mastering the Blame Game in Data and Analytic Teams Welcome, dear readers, to the hallowed halls of Data Buck-Passing University, where the motto is "Per Alios Culpa Transfertur" (Blame is Transferred to Others). In the world of data...
ON DEMAND WEBINAR: Beyond Data Observability
Navigating the Chaos of Unruly Data: Solutions for Data Teams
The Perilous State of Today’s Data Environments Data teams often navigate a labyrinth of chaos within their databases. The core issue plaguing many organizations is the presence of out-of-control databases or data lakes characterized by: Unrestrained Data Changes:...
ON DEMAND WEBINAR: Data Observability Demo Day
The Need For Personalized Data Journeys for Your Data Consumers
In today's data-driven landscape, Data and Analytics Teams increasingly face a unique set of challenges presented by Demanding Data Consumers who require a personalized level of Data Observability. As opposed to receiving one-size-fits-all status updates, these key...
