Remove Data Governance Remove Data Strategy Remove Risk
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It’s 2025. Are your data strategies strong enough to de-risk AI adoption?

CIO Business Intelligence

Lack of oversight establishes a different kind of risk, with shadow IT posing significant security threats to organisations. There is, however, another barrier standing in the way of their ambitions: data readiness. Strong data strategies de-risk AI adoption, removing barriers to performance.

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Accelerating AI at scale without sacrificing security

CIO Business Intelligence

By eliminating time-consuming tasks such as data entry, document processing, and report generation, AI allows teams to focus on higher-value, strategic initiatives that fuel innovation. Above all, robust governance is essential.

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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.

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Where CIOs should place their 2025 AI bets

CIO Business Intelligence

As gen AI heads to Gartners trough of disillusionment , CIOs should consider how to realign their 2025 strategies and roadmaps. The World Economic Forum shares some risks with AI agents , including improving transparency, establishing ethical guidelines, prioritizing data governance, improving security, and increasing education.

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Data distilleries: CIOs turn to new efficient enterprise data platforms

CIO Business Intelligence

An analysis uncovered that the root cause was incomplete and inadequately cleaned source data, leading to gaps in crucial information about claimants. This issue resulted in incorrect risk assessments, where high-risk claims were mistakenly approved, and legitimate claims were wrongly flagged as fraudulent.

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Is your data strategy ready for gen AI? LOB leaders may disagree

CIO Business Intelligence

Rapid advancements in artificial intelligence (AI), particularly generative AI are putting more pressure on analytics and IT leaders to get their houses in order when it comes to data strategy and data management. But the enthusiasm must be tempered by the need to put data management and data governance in place.

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HEMA accelerates their data governance journey with Amazon DataZone

AWS Big Data

Initially, the data inventories of different services were siloed within isolated environments, making data discovery and sharing across services manual and time-consuming for all teams involved. Implementing robust data governance is challenging. Oghosa Omorisiagbon is a Senior Data Engineer at HEMA.