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.
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.
Today, Bristol Myers Squib (BMS) has fully acquired Karuna Therapeutics. We congratulate our customer on an amazing success.
DataKitchen’s DataOps services are designed to empower teams at various stages of their DataOps adoption, providing a flexible and comprehensive roadmap to operational excellence
The new idea showcased in the third edition of the DataOps Cookbook is to focus first on understanding and observing the journey that data takes through your production environment – from ingestion to processing to delivering actionable insights. The DataOps Cookbook-‘Data Journey First DataOps’ Third Edition
On 20 July 2023, Gartner released the article “Innovation Insight: Data Observability Enables Proactive Data Quality” by Melody Chien.
DataKitchen Summarizes and comments
The Ten Standard Tools To Develop Data Pipelines In Microsoft Azure. Is it overkill? Paradox of choice? Or the right tool for the right job? We discuss.
What is the full range of data quality validation tests for data at rest and data in use? Linguistics provides an organizing principle: syntax, semantics, and pragmatics
‘Data Journey First DataOps’: it’s a revolution in which every data, tool, server, and step becomes part of a meaningful story, enhancing our data initiatives’ overall value, impact, and trust.
The benefits of a long-lasting relationship between Data Journeys and data lineage can help give a complete view of your data operations. Both tools help deliver more trusted insight to your customer.
DataOps Observability: Monitor every Data Journey in an enterprise, from source to customer value, and find errors fast! [Open Source, Enterprise]
DataOps TestGen: Simple, Fast Data Quality Test Generation and Execution. Trust, but verify your data! [Open Source, Enterprise]
DataOps Automation: Orchestrate and automate your data toolchain to deliver insight with few errors and a high rate of change. [Enterprise]
DataOps Consulting, Coaching, and Transformation
Commercial Pharma Agile Data Warehouse
Data Production Teams
Data Science/AI
Data Engineering
Data Quality
Business Analytics
Data Products
Data Mesh
Data Contracts
ModelOps / MLOps
Data Observability
DataGovOps
Self-Service Operations
Hybrid Cloud Architectures
Cloud Architectures
Kubernetes Architectures
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.