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...
Cynozure’s James Lupton joins us to discuss how DataOps is a critical element of any data strategy, especially if your goal is to deliver high-quality data products at pace.
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,...
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,...
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...
Jesse Anderson of the Big Data Institute talks about how to organize your data team for DataOps success.
Data privacy experts Peter Lancos and Sonal Rattan of eXate, join Chris Bergh of DataKitchen to discuss the what, why, and how of DataSecOps.
DataOps thought leader, Lars Albertsson, shares his DataOps experience at Spotify, including what worked, what didn’t, and key lessons learned along the way.
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
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.