Data Engineering DataOps Information 
Dataconomy
MAY 26, 2025
Big data engineers are essential in today’s data-driven landscape, transforming vast amounts of information into valuable insights. As businesses increasingly depend on big data to tailor their strategies and enhance decision-making, the role of these engineers becomes more crucial.
Dataversity
MAY 16, 2025
Data products are proliferating in the enterprise, and the good news is that users are consuming data products at an accelerated rate, whether its an AI model, a BI interface, or an embedded dashboard on a website.
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Alation
SEPTEMBER 28, 2022
What exactly is DataOps ? The term has been used a lot more of late, especially in the data analytics industry, as we’ve seen it expand over the past few years to keep pace with new regulations, like the GDPR and CCPA. In essence, DataOps is a practice that helps organizations manage and govern data more effectively.
Alation
MARCH 22, 2022
Data people face a challenge. They must put high-quality data into the hands of users as efficiently as possible. DataOps has emerged as an exciting solution. As the latest iteration in this pursuit of high-quality data sharing, DataOps combines a range of disciplines. Accenture’s DataOps Leap Ahead.
Alation
JUNE 21, 2022
The audience grew to include data scientists (who were even more scarce and expensive) and their supporting resources (e.g., ML and DataOps teams). After that came data governance , privacy, and compliance staff. Power business users and other non-purely-analytic data citizens came after that. data pipelines) to support.
Alation
APRIL 4, 2023
Now, joint users will get an enhanced view into cloud and data transformations , with valuable context to guide smarter usage. At the heart of this release is the need to empower people with the right information at the right time. To build effective data pipelines, they need context (or metadata) on every source.
Alation
DECEMBER 13, 2022
So feckless buyers may resort to buying separate data catalogs for use cases like…. Data governance. For example, the researching buyer may seek a catalog that scores 6 for governance, 10 for self-service, 4 for cloud data migration, and 2 for DataOps (let’s call this a {6, 10, 4, 2} profile). Self-service.
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