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.

DataOps 52

DataOps Data Pipeline Data Engineering Data Engineer 52

Dataversity

SEPTEMBER 8, 2023

Data Management has never been more critical than today. As AI grows more prominent, data initiatives are more important than ever. As the digital age propels us forward, the need for robust DataOps strategies becomes evident. Data-focused practitioners have a unique relationship with data.

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DataOps AI AI Cloud Data 62

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.

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DataOps Data Scientist Data Quality Data Pipeline 52

Dataversity

MARCH 29, 2021

The post The Move to Public Cloud and an Intelligent Data Strategy appeared first on DATAVERSITY. Click to learn more about author Joe Gaska. This is especially true when it comes to applications. As […].

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DataOps Data Lakes Azure AWS 94

Alation

JANUARY 25, 2022

On the policy front, a feature like Policy Center empowers users to enforce and track policies at scale; this ensures that people use data compliantly, and organizations are prepared for compliance audits. Automated Data Orchestration (AKA DataOps). Automated data orchestration interweaves data with connecting processes.

DataOps 52

DataOps SQL ML ML 52

Dataversity

FEBRUARY 4, 2021

Currently, many businesses are using public clouds to do their Data Management. Data Management platforms (DMPs) started becoming popular during the late 1990s and the early 2000s. Click to learn more about author Keith D.

Data Observability 59

Data Observability DataOps Cloud Data Analytics 59

Alation

APRIL 4, 2023

Building data pipelines is challenging, and complex requirements (as well as the separation of many sources) leads to a lack of trust. Troubleshooting data issues , for an exploding number of disjointed systems and tools, breaks self-service for data users and creates gaps in visibility for dataOps.

DataOps 52

DataOps Data Engineering Data Engineer Data Engineering 52