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The Top 7 CIO Priorities for Data and AI in 2025
As we step into 2025, the role of Chief Information Officers (CIOs) continues to evolve in tandem with the rapid advancements in technology. Data and Artificial Intelligence (AI) remain at the core of this transformation, driving innovation, efficiency, and competitive advantage. For CIOs, navigating this dynamic landscape requires a focus on key priorities that balance operational excellence with strategic foresight.
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How Metadata Enhances AI Model Accuracy
AI requires massive amounts of data to train its models. The AI-powered outcomes are untrustworthy if trained on low-quality, mismatched, or otherwise “bad” data. Therefore, understanding data before using it as an input for AI applications is crucial, and metadata is the key.
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The 4 Pillars of Data Lineage: How Alation Catalogs Your Data's Journey
Data is at the core of every modern business decision, but without visibility into where it comes from, how it changes, and where it’s used, organizations risk making decisions based on incomplete or inaccurate information. Data lineage provides the critical transparency needed to track the end-to-end journey of data—from raw ingestion to transformation, reporting, and beyond. With a clear view of data movement and dependencies, businesses can drive better governance, improve data quality, and accelerate data-driven innovation.
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The Modern Data Stack Explained: What to Know in 2025
Key takeaways
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What Is a Data Product Operating Model? A Step-by-Step Guide
The world of data management is rapidly changing, pushing organizations to rethink how they extract value from their data. A key driver of this transformation (along with AI) is the rise of data products. According to the Gartner Chief Data and Analytics Officer (CDAO) Agenda Survey 2024, 50% of organizations have already deployed data products, and another 29% are actively considering them.
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What Are AI Agents? Why Do They Need Trusted Data to Succeed?
AI agents are autonomous systems designed to perform tasks and make decisions by processing data and learning from their environments.
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The Data Scientist’s Guide to the Data Catalog in 2025
In today’s data-driven world, data scientists are rock stars as they shape the future and command top salaries. But even these heavy hitters have a common obstacle: finding and trusting the right data to do their jobs.
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Challenges and Concepts in Enterprise Knowledge Discovery
In today's data-driven enterprises, the quest for critical knowledge often feels like searching for a needle in a haystack. Employees routinely spend countless hours hunting for relevant data, resulting in a significant productivity drain. Modern organizations can ill afford this inefficiency.
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Data Quality Management for AI Success: Your 2025 Guide
Why is data quality important for businesses today?
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