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Why Is Data Architecture Important for the Success of AI?

Dataiku

If there’s one thing we’ve learned at Dataiku after talking to thousands of prospects and customers about their data architecture it’s that architecture frameworks tend to be more aspirational than realistic because, at the enterprise level, data architecture is both complex and constantly changing.

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Join us at the Iceberg Summit 2024

Cloudera

Iceberg, a high-performance open-source format for huge analytic tables, delivers the reliability and simplicity of SQL tables to big data while allowing for multiple engines like Spark, Flink, Trino, Presto, Hive, and Impala to work with the same tables, all at the same time. The Iceberg community is deeply important to us at Cloudera.

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What is a Data Mesh?

DataKitchen

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. DataOps helps the data mesh deliver greater business agility by enabling decentralized domains to work in concert. . But first, let’s define the data mesh design pattern.

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How BayCare Health System excels in raising data literacy

CIO Business Intelligence

Martha Heller: What does data literacy mean to BayCare Health System? When the environmental services team who cleans our operating rooms has the data to flip an OR quickly to get a new patient in, they work more efficiently. What data is most important for you right now? We’re using data to reduce that wait time.

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Implementing a Pharma Data Mesh using DataOps

DataKitchen

Below is our fourth post (4 of 5) on combining data mesh with DataOps to foster innovation while addressing the challenges of a decentralized architecture. We’ve covered the basic ideas behind data mesh and some of the difficulties that must be managed. Figure 1: Data requirements for phases of the drug product lifecycle.

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Business Strategies for Deploying Disruptive Tech: Generative AI and ChatGPT

Rocket-Powered Data Science

It is important to realize that the usual “hype cycle” rules prevail in such cases as this. Third, any commitment to a disruptive technology (including data-intensive and AI implementations) must start with a business strategy. 2) Why should your organization be doing it and why should your people commit to it? (2)

Strategy 289
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How IBM is helping accelerate AI adoption and application centric connectivity

IBM Big Data Hub

That’s why, alongside the GSMA , IBM recently announced a new collaboration to support the adoption of and skills for generative artificial intelligence (AI) in the telecom industry through the launch of GSMA Advance’s AI Training program and the GSMA Foundry Generative AI program. The telecom industry is no exception.