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Top 10 Metadata Management Influencers, Sites, and Blogs You Must Follow in 2021

Octopai

Aptly named, metadata management is the process in which BI and Analytics teams manage metadata, which is the data that describes other data. In other words, data is the context and metadata is the content. Without metadata, BI teams are unable to understand the data’s full story.

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The Key to Faster Impact Analysis: Automated Data Lineage

Octopai

With the insurance company’s current data architecture, the process would have no chance of being completed in time for the change. Watch our webinar to hear how your peers are doing it! Download the webinar. Automated Data Lineage Reduces Total Time to a Fraction. Impact Analysis Research in 1 Day Instead of 100?

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Migrating Data to the Cloud: Things You Need to Know

Alation

If an enterprise doesn’t have visibility into data, then the process can become time-consuming and costly. With a good plan and a modern data catalog, you can minimize the time and cost of cloud migration. Source: Webinar with data expert Ibby Rahmani: Emerging Trends in Data Architecture: What’s the Next Big Thing?

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The Future of the Data Lakehouse – Open

Cloudera

In recent years, the term “data lakehouse” was coined to describe this architectural pattern of tabular analytics over data in the data lake. In a rush to own this term, many vendors have lost sight of the fact that the openness of a data architecture is what guarantees its durability and longevity.

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The Future of the Data Lakehouse – Open

CIO Business Intelligence

In recent years, the term “data lakehouse” was coined to describe this architectural pattern of tabular analytics over data in the data lake. In a rush to own this term, many vendors have lost sight of the fact that the openness of a data architecture is what guarantees its durability and longevity.

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5 Data Governance Mistakes to Avoid

Alation

More specifically, it describes the process of creating, administering, and adapting a comprehensive plan for how an organization’s data will be managed. In this way, data governance has implications for a wide range of data management disciplines, including data architecture, quality, security, metadata, and more.

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Breaking State and Local Data Silos with Modern Data Architectures

Cloudera

Modern data architectures. To eliminate or integrate these silos, the public sector needs to adopt robust data management solutions that support modern data architectures (MDAs). Deploying modern data architectures. Lack of sharing hinders the elimination of fraud, waste, and abuse.