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Get the best value from your data by reducing risk and building trust

CIO Business Intelligence

Data privacy encompasses controlling data from unauthorized access, obtaining consent from data subjects as required, and ensuring data integrity. According to a recent IDC Infobrief , 60% of enterprises are now addressing regulations for the use of data as a top priority.

Risk 87
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Who’s paying your data integration tax?

CIO Business Intelligence

Though we know who’s paying your income taxes this April (sorry to rub it in: it’s you), we have to ask: Who’s paying your data integration tax? Data integration tax is a term used to describe the hidden costs associated with integrating data solutions to process your data from disparate sources and for different needs.

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CIO insights: What’s next for AI in the enterprise?

CIO Business Intelligence

CIOs are under increasing pressure to deliver AI across their enterprises – a new reality that, despite the hype, requires pragmatic approaches to testing, deploying, and managing the technologies responsibly to help their organizations work faster and smarter. The top brass is paying close attention.

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The importance of data ingestion and integration for enterprise AI

IBM Big Data Hub

Companies still often accept the risk of using internal data when exploring large language models (LLMs) because this contextual data is what enables LLMs to change from general-purpose to domain-specific knowledge. This may also entail working with new data through methods like web scraping or uploading.

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Managing risk in machine learning

O'Reilly on Data

As the data community begins to deploy more machine learning (ML) models, I wanted to review some important considerations. We recently conducted a survey which garnered more than 11,000 respondents—our main goal was to ascertain how enterprises were using machine learning. Data Platforms. Model lifecycle management.

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A simplified view of the enterprise tech market

CIO Business Intelligence

I hate the way enterprise IT industry analysts see the world. But it’s something that I not only feel myself, but that I hear (in various forms) from tech vendors and enterprise IT execs alike — all the time. The problem is that this process completely ignores the enterprise IT leader’s reality. So, let’s break the paradigm.

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Why data governance is essential for enterprise AI

IBM Big Data Hub

The recent success of artificial intelligence based large language models has pushed the market to think more ambitiously about how AI could transform many enterprise processes. However, consumers and regulators have also become increasingly concerned with the safety of both their data and the AI models themselves.