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White Paper: A New, More Effective Approach To Data Quality Assessments
Embracing a fundamentally different approach that prioritizes influence over enforcement, iteration over perfection, and advocacy over bureaucracy, that empowers you to take control of data quality assessments.
DataKitchen Is One Of The Coolest DataOps & Data Observability Companies of 2025
We’re thrilled to share that DataKitchen has once again been named one of the Coolest DataOps & Data Observability Companies for 2025 by CRN!
DataOps Observability: Taming the Chaos (Part 4)
Part 4: Reviewing the Benefits This is the final post in DataKitchen's four-part series on DataOps Observability. Observability is a methodology for providing visibility of every journey that data takes from source to customer value across every tool, environment,...
Question: What is the difference between Data Quality and DataOps Observability?
Question: What is the difference between Data Quality and Observability in DataOps? Data Quality is static. It is the measure of data sets at any point in time. Data Observability is dynamic -- it is the testing of data, integrated data, and tools acting upon data...
DataOps Observability: Taming the Chaos (Part 3)
Part 3: Considering the Elements of Data Journeys This is the third post in DataKitchen's four-part series on DataOps Observability. Observability is a methodology for providing visibility of every journey that data takes from source to customer value across every...
“Stick Little Thermometers in your Data Journeys”
Question: What is something the data industry is missing? I think it's observability-led DataOps. I've come to believe that we, as an industry, will not change how people build things they've already made. They're already being Heroes and have pain, unhappiness,...
DataOps Observability: Taming the Chaos (Part 2)
Part 2: Introducing Data Journeys This is the second post in DataKitchen's four-part series on DataOps Observability. Observability is a methodology for providing visibility of every journey that data takes from source to customer value across every tool, environment,...
The Perils of Heroic Data Work: Just Say, “Eww.”
The Perils of Heroic Data Work: Just Say, "Eww." We've all been there. You're up against a deadline, working tirelessly to get the job done. But what happens when that "job" leaves a hairball of technical debt that will need to be fixed and improved tomorrow? And what...
DataOps Observability: Taming the Chaos (Part 1)
Part 1: Defining the Problems This is the first post in DataKitchen's four-part series on DataOps Observability. Observability is a methodology for providing visibility of every journey that data takes from source to customer value across every tool, environment, data...
DataOps Mission Control And Managing Your Data Infrastructure Risk
Data Teams can't answer very basic questions about the many, many pipelines they have in production and in development. For example: Data Is there a troublesome pipeline (lots of errors, intermittent errors)? Did my source files/data arrive on time? Is the data in...
DataKitchen Named a Representative Vendor in the 2022 Gartner® Data and Analytics Essentials: #DataOps Report
Fire Your Super-Smart Data Consultants with DataOps
Analytics are prone to frequent data errors and deployment of analytics is slow and laborious. The strategic value of analytics is widely recognized, but the turnaround time of analytics teams typically can’t support the decision-making needs of executives coping with...
DataOps with Matillion and DataKitchen
The Matillion data integration and transformation platform enables enterprises to perform advanced analytics and business intelligence using cross-cloud platform-as-a-service offerings such as Snowflake. The DataKitchen DataOps Platform provides a way to extend...
DataOps For Business Analytics Teams
Business analysts often find themselves in a no-win situation with constraints imposed from all sides. Their business unit colleagues ask an endless stream of urgent questions that require analytic insights. Business analysts must rapidly deliver value and...
