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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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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.

DataOps 52
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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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Supercharge your data strategy: Integrate and innovate today leveraging data integration

IBM Journey to AI blog

This adaptability allows organizations to align their data integration efforts with distinct operational needs, enabling them to maximize the value of their data across diverse applications and workflows. Organizations must support quality enhancement across structured, semistructured and unstructured data alike.

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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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Building and Scaling Gen AI Applications with Simplicity, Performance and Risk Mitigation in Mind Using Iguazio (acquired by McKinsey) and MongoDB

Iguazio

MongoDB for end-to-end AI data management MongoDB Atlas , an integrated suite of data services centered around a multi-cloud NoSQL database, enables developers to unify operational, analytical, and AI data services to streamline building AI-enriched applications. In the end, we’ll provide resources on how to get started.

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