DataOps Data Quality TestGen:
Simple, Fast, Generative Data Quality Testing, Execution, and Scoring.
[Open Source, Enterprise]
DataOps Observability:
Monitor every date pipeline, from source to customer value, & find problems fast
[Open Source, Enterprise]
DataOps Automation:
Orchestrate and automate your data toolchain 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
DataGovOps
Self-Service Operations
Data Quality Assessments
Data Quality Testing
Data Observability
Data Orchestration
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.
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...
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,...
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...
So you’ve got a special data nerd in your life - congrats! They’re great to keep around for mental math, household finances, and lots of Star Trek jokes. We’re kidding - the data nerd is not a monolith. They come in all shapes, sizes, and nerd varieties. We’ve got...
Implementing DataOps requires a combination of new methods and automation that augment an enterprise’s existing toolchain. The fastest and most effective way to realize the benefits of DataOps is to adopt an off-the-shelf DataOps Platform. Some organizations try to...
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...
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...
Since the term was coined, DataOps has expanded the way that people think about data analytics teams and their potential. 2020 was a huge year in DataOps industry acceptance. Media mentions of DataOps are on track to increase 52% over the prior year. To date in 2020,...
As DataOps continues to gain exposure, people are encountering the term for the first time. Below is our list of the most common questions that we hear about DataOps. What is DataOps? DataOps is a collection of technical practices, workflows, cultural norms, and...
Rajesh Gill, Associate Director of Commercial Insights, discusses how Celgene used DataOps to build a huge success with the Otezla brand.
