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Databricks’ new data lakehouse aims at media, entertainment sector

CIO Business Intelligence

The other 10% represents the effort of initial deployment, data-loading, configuration and the setup of administrative tasks and analysis that is specific to the customer, the Henschen said. The joint solution with Labelbox is targeted toward media companies and is expected to help firms derive more value out of unstructured data.

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Exploring real-time streaming for generative AI Applications

AWS Big Data

This data store provides your organization with the holistic customer records view that is needed for operational efficiency of RAG-based generative AI applications. For building such a data store, an unstructured data store would be best. This is typically unstructured data and is updated in a non-incremental fashion.

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Your Data Architecture Holds the Key to Unlocking AI’s Full Potential

CIO Business Intelligence

Businesses that lead in fully deploying AI will be able to optimize customer experiences and efficiencies that help maximize customer retention and customer acquisition and gain a distinct advantage over the competition. In order to move AI forward, we need to first build and fortify the foundational layer: data architecture.

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Get maximum value out of your cloud data warehouse with Amazon Redshift

AWS Big Data

In this post, we look at three key challenges that customers face with growing data and how a modern data warehouse and analytics system like Amazon Redshift can meet these challenges across industries and segments. Nasdaq’s massive data growth meant they needed to evolve their data architecture to keep up.

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Building a Beautiful Data Lakehouse

CIO Business Intelligence

As a result, users can easily find what they need, and organizations avoid the operational and cost burdens of storing unneeded or duplicate data copies. Newer data lakes are highly scalable and can ingest structured and semi-structured data along with unstructured data like text, images, video, and audio.

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Chose Both: Data Fabric and Data Lakehouse

Cloudera

First, organizations have a tough time getting their arms around their data. More data is generated in ever wider varieties and in ever more locations. Organizations don’t know what they have anymore and so can’t fully capitalize on it — the majority of data generated goes unused in decision making. Better together.

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How Cloudera Data Flow Enables Successful Data Mesh Architectures

Cloudera

Those decentralization efforts appeared under different monikers through time, e.g., data marts versus data warehousing implementations (a popular architectural debate in the era of structured data) then enterprise-wide data lakes versus smaller, typically BU-Specific, “data ponds”.

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