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The Data Quality Coffee Series With Uncle Chip
Pull up a chair, pour yourself a fresh cup, and get ready to talk shop—because it’s time for Data Quality Coffee Series with Uncle Chip.

Data Quality When You Don’t Understand the Data: Data Quality Coffee With Uncle Chip #3
You can’t test for what you don’t understand. And so, we don’t. We skip it. We assume. Or worse, we wait until something breaks. What is the solution? Uncle Chip tells!
DataOps Enables Your Data Fabric
Industry analysts who follow the data and analytics industry tell DataKitchen that they are receiving inquiries about “data fabrics” from enterprise clients on a near-daily basis. Forrester relates that out of 25,000 reports published by the firm last year, the report...
The Journey to DataOps Success: Key Takeaways from Transformation Trailblazers
In early April 2021, DataKItchen sat down with Jonathan Hodges, VP Data Management & Analytics, at Workiva; Chuck Smith, VP of R&D Data Strategy at GlaxoSmithKline (GSK); and Chris Bergh, CEO and Head Chef at DataKitchen, to find out about their enterprise...
The DataOps Vendor Landscape, 2021
Download the 2021 DataOps Vendor Landscape here. Read the complete blog below for a more detailed description of the vendors and their capabilities. DataOps is a hot topic in 2021. This is not surprising given that DataOps enables enterprise data teams to generate...
Managing Data Analytics Is More Like Running A Restaurant Than You Think
Gartner – Top Trends in Data & Analytics for 2021: XOps
Gartner identified XOps (DataOps, ModelOps, DevOps) as one of the top trends in data and analytics for 2021. Below we provide additional suggestions for further reading based on Gartner’s recommendations. What is XOps? Gartner: “The multiplication of Ops disciplines...
How DataOps Kitchens Enable Version Control
This blog builds on earlier posts that defined Kitchens and showed how they map to technical environments. We’ve also discussed how toolchains are segmented to support multiple kitchens. DataOps automates the source code integration, release, and deployment workflows...
Pitching a DataOps Project That Matters
Every DataOps initiative starts with a pilot project. How do you choose a project that matters to people? DataOps addresses a broad set of use cases because it applies workflow process automation to the end-to-end data-analytics lifecycle. DataOps reduces errors,...
DataOps Reports that Keep Your Finger on the Pulse
It’s never good when your boss calls at 5 pm on a Friday. “The weekly analytics didn’t build correctly. What happened? Call me every hour with updates until you figure it out!” For many data professionals, this situation is all too familiar. Analytics, in the modern...
Do You Need a DataOps Dojo?
As DataOps activity takes root within an enterprise, managers face the question of whether to build centralized or decentralized DataOps capabilities. Centralizing analytics brings it under control but granting analysts free reign is necessary to foster innovation and...
The Business Case for DataOps
Savvy executives maximize the value of every budgeted dollar. Decisions to invest in new tools and methods must be backed up with a strong business case. As data professionals, we know the value and impact of DataOps: streamlining analytics workflows, reducing errors,...
DataOps Facilitates Remote Work
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...
Gartner: Operational AI Requires Data Engineering, DataOps, and Data-AI Role Alignment
In Gartner’s recent report, Operational AI Requires Data Engineering, DataOps, and Data-AI Role Alignment, Robert Thanaraj and Erick Brethenoux recognize that “organizations are not familiar with the processes needed to scale and promote artificial intelligence models...