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Discover And De-Clutter Your Unstructured Data With Aparavi

Data Engineering Podcast

Summary Unstructured data takes many forms in an organization. From a data engineering perspective that often means things like JSON files, audio or video recordings, images, etc. What are some of the insights that you are able to provide about an organization’s data? Closing Announcements Thank you for listening!

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Bring Order To The Chaos Of Your Unstructured Data Assets With Unstruk

Data Engineering Podcast

Summary Working with unstructured data has typically been a motivation for a data lake. Kirk Marple has spent years working with data systems and the media industry, which inspired him to build a platform for automatically organizing your unstructured assets to make them more valuable.

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Unstructured Data: The Must-Have For Analytics In 2022

KDnuggets

Let's investigate the current need that enterprise organizations have to rapidly parse through unstructured data and examine several data management trends that are highly relevant in 2022.

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Manage Your Unstructured Data Assets Across Cloud And Hybrid Environments With Komprise

Data Engineering Podcast

Summary There are a wealth of options for managing structured and textual data, but unstructured binary data assets are not as well supported across the ecosystem. With simple pricing, fast networking, object storage, and worldwide data centers, you’ve got everything you need to run a bulletproof data platform.

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Convert Your Unstructured Data To Embedding Vectors For More Efficient Machine Learning With Towhee

Data Engineering Podcast

Embedding vectors are a way to structure data in a way that is native to how models interpret and manipulate information. In this episode Frank Liu shares how the Towhee library simplifies the work of translating your unstructured data assets (e.g. The Data Engineering Podcast covers the latest on modern data management.

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The Pros and Cons of Leading Data Management and Storage Solutions

The Modern Data Company

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing.

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The Pros and Cons of Leading Data Management and Storage Solutions

The Modern Data Company

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing.