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Why Your Master Data Management Needs Data Governance

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With cloud computing, the capacity to extract value from data is greater than ever. As this realization grows, businesses are shifting their investments from hardware to technologies that optimize data assets. Master Data Management systems (MDM) play an important role in harmonizing data assets across large and midsize enterprises.

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Unraveling the Threads: Data Fabric vs Data Mesh for Modern Enterprises

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Key Takeaways Data fabric and data mesh are modern data management architectures that allow organizations to more easily understand, create, and manage data for more timely, accurate, consistent, and contextual data analytics and operations. The choice between the two depends on your business needs.

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Simplifying Data Integration Through Eventual Connectivity

Data Engineering Podcast

Rather than manually defining all of the mappings ahead of time, we can rely on the power of graph databases and some strategic metadata to allow connections to occur as the data becomes available. If you are struggling to maintain a tangle of data pipelines then you might find some new ideas for reducing your workload.

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Setting The Stage For The Next Chapter Of The Cassandra Database

Data Engineering Podcast

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode.

Database 100
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Dat: Distributed Versioned Data Sharing with Danielle Robinson and Joe Hand - Episode 16

Data Engineering Podcast

Your host is Tobias Macey and today I’m interviewing Danielle Robinson and Joe Hand about Dat Project, a distributed data sharing protocol for building applications of the future Interview Introduction How did you get involved in the area of data management? What is the Dat project and how did it get started?

Data 100
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Mainframe Data: Empowering Democratized Cloud Analytics

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As a result, there is a widespread desire for access to timely, trustworthy data and the analytical tools to interpret it. This has compelled business users to expand their knowledge of data management and enhance their analytics skills. This can add stress to data management teams and data governance processes.

Cloud 72