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Fire Your Super-Smart Data Consultants with DataOps

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

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

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

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

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

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

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

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

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...

What Is ‘Equity As Code,’ And How Can It Eliminate AI Bias?

What Is ‘Equity As Code,’ And How Can It Eliminate AI Bias?

This article was originally published in Forbes. Engineers unleashed artificial intelligence (AI) bias, and it will be engineers who design the solutions that eliminate it. Authors of an article published by McKinsey Global Institute assert that “more human vigilance...

Infographic – Data Engineers are Burned Out and Calling for DataOps

Infographic – Data Engineers are Burned Out and Calling for DataOps

A survey commissioned by data.world and DataKitchen reveals a disturbing state of affairs among data engineering professionals. The study of 600 data engineers, conducted by Wakefield Research, suggests an overwhelming majority are burned out and calling for relief....

A Day in the Life of a DataOps Engineer

A Day in the Life of a DataOps Engineer

A DataOps implementation project consists of three steps. First, you must understand the existing challenges of the data team, including the data architecture and end-to-end toolchain. Second, you must establish a definition of “done.” In DataOps, the definition of...

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