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Building A Data Governance Bridge Between Cloud And Datacenters For The Enterprise At Privacera

Data Engineering Podcast

Summary Data governance is a practice that requires a high degree of flexibility and collaboration at the organizational and technical levels. The growing prominence of cloud and hybrid environments in data management adds additional stress to an already complex endeavor.

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Octopai Acquisition Enhances Metadata Management to Trust Data Across Entire Data Estate

Cloudera

In today’s heterogeneous data ecosystems, integrating and analyzing data from multiple sources presents several obstacles: data often exists in various formats, with inconsistencies in definitions, structures, and quality standards.

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Data governance beyond SDX: Adding third party assets to Apache Atlas

Cloudera

In this blog, we’ll highlight the key CDP aspects that provide data governance and lineage and show how they can be extended to incorporate metadata for non-CDP systems from across the enterprise. The SDX layer of CDP leverages the full spectrum of Atlas to automatically track and control all data assets.

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The last (but not least)”ops” you need for your data : DataGovops

François Nguyen

To finish the trilogy (Dataops, MLops), let’s talk about DataGovOps or how you can support your Data Governance initiative. In every step,we do not just read, transform and write data, we are also doing that with the metadata. Last part, it was added the data security and privacy part.

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Unified Data Governance: The Key to Greater Visibility

Precisely

As you strive to achieve higher levels of data integrity, data governance becomes imperative. What is Data Governance? Robert Seiner, author of Non-Invasive Data Governance and founder of KIK Consulting, defines data governance as “the execution and enforcement of authority over data.”

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Toward a Data Mesh (part 2) : Architecture & Technologies

François Nguyen

TL;DR After setting up and organizing the teams, we are describing 4 topics to make data mesh a reality. How do we build data products ? How can we interoperate between the data domains ? This is really for us the definition of a self serve platform. What you have to code is this workflow !

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Tracking Schema Changes in Iceberg Tables Using Metadata Files

Cloudyard

Read Time: 4 Minute, 21 Second Introduction Managing schema changes is a critical aspect of maintaining data integrity and consistency in dynamic data environments. When using Iceberg tables, every Data Definition Language ( DDL ) operation triggers the generation of a new metadata JSON file that captures the updated structure.