Blog
FITT vs. Fragile: SQL & Orchestration Techniques For FITT Data Architectures
Transform data engineering from a high-stress, “hero saves the day” kind of job into something systematic and predictable that actually scales as your team and business grow. Stop babysitting pipelines: SQL & ELT the FITT Way.
Data Quality Test Coverage In a Medallion Data Architecture
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.
The Five Use Cases in Data Observability: Data Quality in New Data Sources
The Five Use Cases in Data Observability: Data Quality in New Data Sources (#1) Ensuring their quality and integrity before incorporating new data sources into production is paramount. Data evaluation serves as a safeguard, ensuring that only cleansed and...
The Five Use Cases in Data Observability: Overview
Harnessing Data Observability Across Five Key Use Cases The ability to monitor, validate, and ensure data accuracy across its lifecycle is not just a luxury—it’s a necessity. Data observability extends beyond simple anomaly checking, offering deep insights into...
DataOps and Data Observability Education And Certification Offerings From DataKitchen
DataKitchen Training And Certification Offerings For Individual contributors with a background in Data Analytics/Science/Engineering Overall Ideas and Principles of DataOps DataOps Cookbook (200 page book over 30,000 readers, free): DataOps Certification (3...
Webinar Summary: Introducing Open Source Data Observability
Last week's webinar, presented by Christopher Bergh, CEO and Head Chef at DataKitchen, explored the impact of newly released open-source software tools on data operations and analytics. The event was an informative session that dove deep into the functionalities and...
Why We Open-Sourced Our Data Observability Products
Introducing DataKitchen’s Open Source Data Observability Software Today, we announce that we have open-sourced two complete, feature-rich products that solve the data observability problem: DataOps Observervability and DataOps TestGen. With these two products, you...
Webinar Summary: Agile, DataOps, and Data Team Excellence
The hosted by Christopher Bergh with Gil Benghiat from DataKitchen covered a comprehensive range of topics centered around improving the performance and efficiency of data teams through Agile and DataOps methodologies. Gil Benghiat, co-founder of Data Kitchen, began...
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...
