Remote working has revealed the inconsistency and fragility of workflow processes in many data organizations. The data teams share a common objective; to create analytics for the (internal or external) customer. Execution of this mission requires the contribution of...
Recommendations for Further Reading
While 2020 has been a collectively difficult year, we want to take a moment to thank all of our employees for the hard work they put into continually developing our DataKitchen DataOps Platform for our customers. We also want to thank all of the data industry groups...
We understand that many folks would like to say goodbye and good riddance to 2020. But before we shut the door on such a turbulent, transformative year, we at DataKitchen would like to share the creme de la creme of our DataOps content in hopes that it can help you as...
It is not the strongest of the species that survives, nor the most intelligent that survives. It is the one that is most adaptable to change. - Leon C. Megginson on Charles Darwin “Origin of Species” Adapt or face decline. The agile alliance defines “business agility”...
Curious about what DataOps capabilities your organization already has or how you stack up? DataKitchen published a white paper Launch Your DataOps Journey with the DataOps Maturity Model (which you can download here) to guide you on benchmarking your org's DataOps...
So you've learned about DataOps and want to get begin implementing it? Look no further than DataKitchen's white paper The Seven Steps to Implement DataOps (which you can download here)! We've taken the seven steps to implement DataOps and included them in the...
In Forrester’s recent report, DataOps for the Intelligent Edge of Business, Michele Goetz, et al., describe how data teams are facing challenges “about data to support the return on investment and experience.” In fact, “no amount of investment in new big data systems,...
Many adages could be applied to implementing a successful, sustainable DataOps program at your organization, such as 'Rome wasn't built in a day.' or, "Don't boil the ocean." To help you approach introducing DataOps into your organization, we at DataKitchen broke down...
DataOps revolutionizes how data-analytics work gets done. Like many other “big ideas,” it sometimes faces resistance from within the organization. For most organizations, data is a means to an end. The organization’s primary focus is on its mission, whether that is a...
DataOps Observability: Monitor every Data Journey in an enterprise, from source to customer value, and find errors fast! [Open Source, Enterprise]
DataOps Data Quality 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 Data & Analytics Platform for Pharma
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.