Blog
Webinar: A Guide to the Six Types of Data Quality Dashboards
In an exciting webinar, we discuss the six major types of Data Quality Dashboards
Data Quality Testing: A Shared Resource for Modern Data Teams
Data quality is not a problem any single role can solve in isolation. The complexity and scale of modern data ecosystems necessitate a collaborative approach, where quality testing serves as a shared infrastructure across all data and analytics roles.
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...
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...
Eight Top DataOps Trends for 2022
DataOps adoption continues to expand as a perfect storm of social, economic, and technological factors drive enterprises to invest in process-driven innovation. From our unique vantage point in the evolution toward DataOps automation, we publish an annual prediction...
How To Succeed as a DataOps Engineer
What makes an effective DataOps Engineer? A DataOps Engineer shepherds process flows across complex corporate structures. Organizations have changed significantly over the last number of years and even more dramatically over the previous 12 months, with the sharp...
10 DataOps Principles for Overcoming Data Engineer Burnout
For several years now, the elephant in the room has been that data and analytics projects are failing. Gartner estimated that 85% of big data projects fail. Data from New Vantage partners showed that the number of data-driven organizations has actually declined to...
Centralize Your Data Processes With a DataOps Process Hub
Data organizations often have a mix of centralized and decentralized activity. DataOps concerns itself with the complex flow of data across teams, data centers and organizational boundaries. It expands beyond tools and data architecture and views the data organization...
