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

CIO Business Intelligence

Yet, despite growing investments in advanced analytics and AI, organizations continue to grapple with a persistent and often underestimated challenge: poor data quality. Fragmented systems, inconsistent definitions, legacy infrastructure and manual workarounds introduce critical risks.

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AI market evolution: Data and infrastructure transformation through AI

CIO Business Intelligence

AI a primary driver in IT modernization and data mobility AI’s demand for data requires businesses to have a secure and accessible data strategy. Data security, data quality, and data governance still raise warning bells Data security remains a top concern.

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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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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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How ANZ Institutional Division built a federated data platform to enable their domain teams to build data products to support business outcomes

AWS Big Data

This post explores how the shift to a data product mindset is being implemented, the challenges faced, and the early wins that are shaping the future of data management in the Institutional Division. This principle makes sure data accountability remains close to the source, fostering higher data quality and relevance.

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Steps taken to build Sevita’s first enterprise data platform

CIO Business Intelligence

But because of the infrastructure, employees spent hours on manual data analysis and spreadsheet jockeying. We had plenty of reporting, but very little data insight, and no real semblance of a data strategy. This legacy situation gave us two challenges.

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Unlocking the Power of AI with a Real-Time Data Strategy

CIO Business Intelligence

Here, I’ll focus on why these three elements and capabilities are fundamental building blocks of a data ecosystem that can support real-time AI. DataStax Real-time data and decisioning First, a few quick definitions. Real-time data involves a continuous flow of data in motion.