Remove Data-driven Remove Events Remove Gap analysis
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INE Security: Optimizing Teams for AI and Cybersecurity

CIO Business Intelligence

AI systems are invaluable, enabling us to process vast amounts of data with unmatched speed and accuracy, detect anomalies, predict threats, and respond to incidents in real-time. This ensures consistent practice and skill refinement in handling AI-driven security scenarios.

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8 strategies for accelerating IT modernization

CIO Business Intelligence

Think process, not event Modernization remains a constant item on the CIO to-do list, so the task should be a standard part of IT’s schedule. Companies that do well have turned modernization into a process instead of an event. I need one managing data and orchestrating the OEM platform base to drive business results.”

Strategy 140
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How healthcare organizations can analyze and create insights using price transparency data

AWS Big Data

Under the Transparency in Coverage (TCR) rule , hospitals and payors to publish their pricing data in a machine-readable format. The data in the machine-readable files can provide valuable insights to understand the true cost of healthcare services and compare prices and quality across hospitals.

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The art and science of data product portfolio management

AWS Big Data

This post is the first in a series dedicated to the art and science of practical data mesh implementation (for an overview of data mesh, read the original whitepaper The data mesh shift ). Taken together, the posts in this series lay out some possible operating models for data mesh within an organization.

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What’s the Difference: Quantitative vs Qualitative Data

Alation

Companies collect and analyze vast amounts of data to make informed business decisions. From product development to customer satisfaction, nearly every aspect of a business uses data and analytics to measure success and define strategies. When choosing between qualitative and quantitative data, think about what you want to learn.

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Beyond the hype: Key components of an effective AI policy

CIO Business Intelligence

While this leads to efficiency, it also raises questions about transparency and data usage. Data governance Strong data governance is the foundation of any successful AI strategy. This includes regular audits to guarantee data quality and security throughout the AI lifecycle.

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Security is dead: Long live risk management

CIO Business Intelligence

In todays digital economy, business objectives like becoming a trusted financial partner or protecting customer data while driving innovation require more than technical controls and documentation. 2025 Banking Regulatory Outlook, Deloitte The stakes are clear.