Remove Business Analytics Remove Data Engineering Remove Generative AI
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The future of data: A 5-pillar approach to modern data management

CIO

This approach is repeatable, minimizes dependence on manual controls, harnesses technology and AI for data management and integrates seamlessly into the digital product development process. Operational errors because of manual management of data platforms can be extremely costly in the long run.

Data 167
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ChatGPT: le nuove sfide della strategia sui dati nell’era dell’IA generativa

CIO

Le aziende italiane investono in infrastrutture, software e servizi per la gestione e l’analisi dei dati (+18% nel 2023, pari a 2,85 miliardi di euro, secondo l’Osservatorio Big Data & Business Analytics della School of Management del Politecnico di Milano), ma quante sono giunte alla data maturity?

ChatGPT 78
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Technology Trends for 2025

O'Reilly Media - Ideas

Its been an exciting year, dominated by a constant stream of breakthroughs and announcements in AI, and complicated by industry-wide layoffs. Generative AI gets better and betterbut that trend may be at an end. Theres a different take on the future of prompt engineering. That depends on many factors.

Trends 131
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Technology Trends for 2023

O'Reilly Media - Ideas

Data Data is another very broad category, encompassing everything from traditional business analytics to artificial intelligence. Data engineering was the dominant topic by far, growing 35% year over year. Yet here we are, and we don’t have ChatGPT or generative AI in our taxonomy.

Trends 144
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Using Large Language Models on Amazon Bedrock for multi-step task execution

AWS Machine Learning - AI

Traditionally, answering these queries required the expertise of business intelligence specialists and data engineers, often resulting in time-consuming processes and potential bottlenecks. About the Authors Bruno Klein is a Senior Machine Learning Engineer with AWS Professional Services Analytics Practice.

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Data’s dark secret: Why poor quality cripples AI and growth

CIO

Data stewardship drives ownership and embeds trust locally. Create cross-functional data councils. Bring together IT, business, analytics and compliance leaders to guide priorities, resolve disputes and make shared decisions about quality, access and usage. Robust governance ensures consistency without slowing teams down.