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What Is a Data Product Manager?
The explosion of data has reshaped how organizations operate. With data now a critical strategic asset, companies are moving away from traditional data management approaches and embracing data products—structured, reusable, and high-quality data assets designed for specific business purposes.
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Critical Data Elements Explained: Defining, Governing, and Automating CDEs
Organizations are awash in data, but not all data is equally important. Understanding and managing your most vital bits of information is critical to success.
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Is Your Data Operating Model Broken?
In today’s fast-moving business world, the ability to act on data quickly is the difference between capitalizing on an opportunity and missing it altogether. Yet data teams, already overwhelmed by a flood of business requests, find themselves stuck in bottlenecks—too slow to deliver the insights decision-makers need. As demand for data grows, the traditional operating model—where data teams act as gatekeepers, controlling access and enforcing governance—can no longer keep up.
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What Is Ethical AI? A Guide to Responsible AI Development and Governance
The rapid rise of AI is ushering in a new era of business transformation—one filled with both unprecedented opportunities and significant risks. As AI increasingly influences decision-making, companies must navigate a shifting regulatory landscape while ensuring that AI systems are developed and deployed responsibly.
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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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Blog
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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