Most AI initiatives fail not because of technology, but because of poor data governance and this article shows leaders how to build a business-driven data governance strategy that turns AI investments into real, measurable value instead of sunk costs.
This article explains how a structured data cataloging process turns growing organizational complexity into a scalable advantage, providing a practical, phased blueprint to preserve data knowledge, improve productivity, and enable analytics and AI as your company scales.
Augmented data catalogs are next-generation tools that bridge the gap between human expertise and machine intelligence, combining human insight with AI-powered automation. Let’s take a closer look at what they…
The relationship between data lakes and data catalogs is a critical one; they often coexist within the same architecture but serve distinct purposes with different impacts on data management. They…
The time has come – you’re ready to build your data catalog. A big step towards data governance for your company. But how do you communicate the requirements for your…
Data inventory and data catalog: at first glance, the two terms might seem interchangeable. After all, both deal with organizing and managing data assets. But actually, they serve distinct purposes…
If you’re planning to implement a data catalog, pricing is definitely on your mind as you research the available solutions. Here’s a handful of tips on what to look for…
At Murdio, we help companies get the most from their data ecosystems, and this topic comes up constantly – because it’s at the very core of what we do and…
This article shows how Collibra’s AI-powered Text2SQL bridges the gap between business and IT, enabling anyone to create custom data quality checks in plain language and turn unreliable data into a trusted, continuously monitored asset.
Unstructured data is exploding across clouds, drives, and inboxes. This article shows how automated discovery with Collibra and Ohalo turns hidden files into visible, governed, and compliant enterprise assets.
A practical, experience-driven Collibra implementation blueprint that cuts through theory and shows how enterprise data governance succeeds or fails in real life.
A global retailer transformed a fragmented, manual data-access experience into a unified, automated “one-stop shop” that streamlines how employees discover, evaluate, and request data.
A clear, practical introduction to how Collibra Data Governance works, what it enables inside large enterprises, and how real organizations use it to make data more trusted, compliant, and operational at scale.
Organizations rely on increasingly complex data ecosystems – and this means that understanding where their data comes from, how it moves, and how it changes along the way becomes crucial…
A definitive guide to Collibra Data Catalog that explains how it centralizes metadata, enriches business context, automates governance processes, and turns enterprise data into a trusted, governed, and discoverable strategic asset.
AI is now powering everything from customer service chatbots to advanced analytics in healthcare and financial services. But many organizations have already learned first-hand that setting policies around the responsible…
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A data governance framework is the fastest way to turn costly, “dark” data into a governed asset. This guide shows best practices and real examples of how organizations reduce risk, cut waste, and deliver measurable ROI.
Most AI initiatives fail not because of technology, but because of poor data governance and this article shows leaders how to build a business-driven data governance strategy that turns AI investments into real, measurable value instead of sunk costs.
Data observability and data quality solve different risks, one protects the health of your data pipelines, the other the truth of your data, and only together can they make AI decisions reliable at scale.
A data governance policy is the critical foundation that turns chaotic data into trusted, high-quality assets. This guide shows you exactly how to build one that reduces risk, accelerates analytics and AI initiatives, and delivers measurable business impact.
This article shows how Collibra’s AI-powered Text2SQL bridges the gap between business and IT, enabling anyone to create custom data quality checks in plain language and turn unreliable data into a trusted, continuously monitored asset.
This article explains how a structured data cataloging process turns growing organizational complexity into a scalable advantage, providing a practical, phased blueprint to preserve data knowledge, improve productivity, and enable analytics and AI as your company scales.
This article explains the seven foundational pillars of data governance and shows how aligning stewardship, quality, security, architecture, analytics, and culture creates a durable strategy that delivers real business value rather than a box-ticking framework.
This article goes beyond role definitions to show how to formally empower Data Owners, Stewards, and Custodian, turning data governance from a side-of-desk initiative into an accountable, well-resourced system that actually drives trust, quality, and business outcomes.
This 2025 guide breaks down the best data quality tools, what to look for, and how to choose the right platform for your data ecosystem.
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