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It’s 2025. Are your data strategies strong enough to de-risk AI adoption?

CIO Business Intelligence

According to Richard Kulkarni, Country Manager for Quest, a lack of clarity concerning governance and policy around AI means that employees and teams are finding workarounds to access the technology. There is, however, another barrier standing in the way of their ambitions: data readiness.

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Practical Skills for The AI Product Manager

O'Reilly on Data

In our previous article, What You Need to Know About Product Management for AI , we discussed the need for an AI Product Manager. In this article, we shift our focus to the AI Product Manager’s skill set, as it is applied to day to day work in the design, development, and maintenance of AI products. The AI Product Pipeline.

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IT leaders brace for the AI agent management challenge

CIO Business Intelligence

With AI agents poised to take over significant portions of enterprise workflows, IT leaders will be faced with an increasingly complex challenge: managing them. Analysts say the big three hyperscalers and cloud management vendors are aware of the gap and are working on it.

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7 enterprise data strategy trends

CIO Business Intelligence

Every enterprise needs a data strategy that clearly defines the technologies, processes, people, and rules needed to safely and securely manage its information assets and practices. Here’s a quick rundown of seven major trends that will likely reshape your organization’s current data strategy in the days and months ahead.

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The Unexpected Cost of Data Copies

Read this whitepaper to learn: Why organizations frequently end up with unnecessary data copies. How replicated data increases costs and impacts the bottom line. How a next-gen data lake can halt data replication and streamline data management. What to consider when implementing a "no-copy" data strategy.

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Octopai Acquisition Enhances Metadata Management to Trust Data Across Entire Data Estate

Cloudera

In today’s heterogeneous data ecosystems, integrating and analyzing data from multiple sources presents several obstacles: data often exists in various formats, with inconsistencies in definitions, structures, and quality standards.

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8 data strategy mistakes to avoid

CIO Business Intelligence

Organizations can’t afford to mess up their data strategies, because too much is at stake in the digital economy. How enterprises gather, store, cleanse, access, and secure their data can be a major factor in their ability to meet corporate goals. Here are some data strategy mistakes IT leaders would be wise to avoid.