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Improving Data Pipelines with DataOps

Dataversity

It was only a few years ago that BI and data experts excitedly claimed that petabytes of unstructured data could be brought under control with data pipelines and orderly, efficient data warehouses. But as big data continued to grow and the amount of stored information increased every […].

DataOps 59
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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 […].

DataOps 98
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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

A flexible approach that enables tooling coexistence as well as flexibility with locality of pipeline execution with targeted data planes or pushdown of transformation logic to data warehouses or lakehouses decreases unnecessary data movement to reduce or eliminate data egress charges.

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What Is a Data Fabric and How Does a Data Catalog Support It?

Alation

Data fabric is now on the minds of most data management leaders. In our previous blog, Data Mesh vs. Data Fabric: A Love Story , we defined data fabric and outlined its uses and motivations. The data catalog is a foundational layer of the data fabric. Automated Data Orchestration (AKA DataOps).

DataOps 52
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Fabrics, Meshes & Stacks, oh my! Q&A with Sanjeev Mohan

Alation

DataOps sprung up to connect data sources to data consumers. The data warehouse and analytical data stores moved to the cloud and disaggregated into the data mesh. And now with some of these cloud data warehouses becoming such behemoths, everything is getting centralized again.

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How to use Snowflake Zero Copy Cloning in your CI/CD Pipelines

phData

To truly test the effects of a deployment, you need to have an environment with the exact data that is in Production. In this blog, we’ll explore how to properly leverage the Zero Copy Clone feature from the Snowflake Data Cloud. Many open-source and free tools exist, such as Flyway, Liquibase, schemachange, or DataOps.