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DataOps and Scalability: The One-Two Punch for Creating Successful Data Products

Dataversity

The bad news is that too many data engineering teams still rely on manual methods to keep these […] The post DataOps and Scalability: The One-Two Punch for Creating Successful Data Products appeared first on DATAVERSITY.

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Is DataOps the Savior of Under-Pressure Analytics Teams?

Dataversity

DataOps is something that has been building up at the edges of enterprise data strategies for a couple of years now, steadily gaining followers and creeping up the agenda of data professionals. The post Is DataOps the Savior of Under-Pressure Analytics Teams? And many believe it could now finally be about to enter the mainstream.

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Data Operations and DataOps: Not One and the Same

Dataversity

In today’s competitive enterprise landscape, having a proper DataOps strategy in place correlates with better data intelligence and optimization within an organization – breaking down silos and enabling data democratization and better business agility at scale.

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DataOps or Data Fabric: Which Should Your Business Adopt First?

Dataversity

There’s no shortage of buzzwords and phrases to define how an organization approaches and uses its data – with two of the most popular being DataOps and data fabric. The post DataOps or Data Fabric: Which Should Your Business Adopt First? appeared first on DATAVERSITY.

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DataOps Highlights the Need for Automated ETL Testing (Part 2)

Dataversity

DataOps, which focuses on automated tools throughout the ETL development cycle, responds to a huge challenge for data integration and ETL projects in general. The post DataOps Highlights the Need for Automated ETL Testing (Part 2) appeared first on DATAVERSITY. Click to learn more about author Wayne Yaddow. The […].

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DataOps: What It Is and What the Enterprise Gets Wrong

Dataversity

The post DataOps: What It Is and What the Enterprise Gets Wrong appeared first on DATAVERSITY. With this rapid growth, the ability to harness data for business impact is even more vital. To keep up with the exponential data growth and resulting challenges, data teams must adjust the way they operate. […].

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DataOps vs. DevOps: What’s the Difference?

Alation

DataOps and DevOps are two distinctly different pursuits. But where DevOps focuses on product development, DataOps aims to reduce the time from data need to data success. At its best, DataOps shortens the cycle time for analytics and aligns with business goals. What is DataOps? What is DevOps? The Agile Connection.

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