Blog

Only One Problem To Solve for Successful Data and Analytics
The real problem in data analytics is that teams need to
deliver insight to their customers without error
put new ideas into production rapidly
minimize their ‘insight manufacturing’ expenses
… all at the same time

A summary of Gartner’s recent DataOps-driven data engineering best practices article
Gartner released the article “5 Ways to Enhance Your Data Engineering Practices.” By Robert Thanaraj, Ehtisham Zaidi, and 2 more. DataKitchen gives its perspective.
“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
IBM Loves DataOps
DataOps is a discipline focused on the delivery of data faster, better, and cheaper to derive business value quickly. It closely follows the best practices of DevOps although the implementation of DataOps to data is nothing like DevOps to code. This paper will focus...
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...
DataKitchen’s Best of 2021 DataOps Resources
Before we shut the door on 2021, we would like to share our most popular DataOps content in hopes that it can help you as you learn about and implement DataOps. We hope you and your family have happy holidays and we look forward to continuing your DataOps journey with...
2021 Gift Giving Guide for Data Nerds
Back by popular demand, we've updated our data nerd Gift Giving Guide to cap off 2021. We've kept some classics and added some new titles that are sure to put a smile on your data nerd's face. Here are eight highly recommendable books to help you find that special...