Remove Data Management Remove Systems Remove Technology Remove Unstructured Data
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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? When is Aparavi the wrong choice?

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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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Prepare Your Unstructured Data For Machine Learning And Computer Vision Without The Toil Using Activeloop

Data Engineering Podcast

In this episode Davit Buniatyan, founder and CEO of Activeloop, explains why he is spending his time and energy on building a platform to simplify the work of getting your unstructured data ready for machine learning. The data you’re looking for is already in your data warehouse and BI tools.

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Top 5 Data + AI Predictions for Financial Services in 2024

Snowflake

And it’s no wonder — this new technology has the potential to revolutionize the industry by augmenting the value of employee work, driving organizational efficiencies, providing personalized customer experiences, and uncovering new insights from vast amounts of data. Here are just a few of their exciting predictions for the year ahead.

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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. eventual consistency vs. read-after-write, low latency replication on data changes vs. scheduled syncing, etc.)

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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.