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What Is DataOps? Definition, Principles, and Benefits

Alation

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.

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Turnkey Cloud DataOps: Solution from Alation and Accenture

Alation

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.

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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 Highlights the Need for Automated ETL Testing (Part 1)

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 1) appeared first on DATAVERSITY. Click to learn more about author Wayne Yaddow. The […].

DataOps 52
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How Data Observability Helps to Build Trusted Data

Precisely

Trusted data is crucial, and data observability makes it possible. Data observability is a key element of data operations (DataOps). Read Data Observability vs. Data Quality Given they share similar aims, it might be easy to conflate the idea of data observability with data quality.

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The Audience for Data Catalogs and Data Intelligence

Alation

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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What Is Data Observability and Why You Need It?

Precisely

Systems and data sources are more interconnected than ever before. A broken data pipeline might bring operational systems to a halt, or it could cause executive dashboards to fail, reporting inaccurate KPIs to top management. Data observability is a foundational element of data operations (DataOps).