Insights
How to convert unstructured data to structured data
Don't just extract data - govern it. A complete guide on how to convert unstructured data while managing PII risks and preventing hallucinations.
Articles:
Collibra
The definitive guide to the Collibra and SAP alliance
SAP delivers data at scale. Collibra makes it usable, trustworthy, and safe. Learn how their alliance enables governed analytics and AI across complex enterprise data landscapes.
Collibra
Why Collibra adoption fails (and how to fix it in 2026)
A frequent scenario we see is this: an enterprise buys Collibra, but it ends up underused or not used at all. Here’s how to handle Collibra adoption so that this doesn’t happen.
Collibra
How to choose the right Collibra Reseller
Here’s what to look for when buying your Collibra license and – more importantly – what comes next.
Case Study
Case Study: Migrating a custom Data Marketplace to Collibra for a pharma company
See how a global organization replaced a custom-built web application with a Collibra-powered Data Marketplace to reduce maintenance costs, maximize software ROI, and standardize data access for hundreds of users.
Case Study
Case Study: Transforming Collibra Data Marketplace for a chemical manufacturer
See how a multinational company replaced a "patchwork" of isolated workflows with a sophisticated, user-friendly Data Marketplace in Collibra that automates complex approval chains and guides users through every step of the data access journey.
Data Governance
Data governance best practices
Most companies have data governance policies - few have governance that actually works. This article breaks down the practical habits, automation strategies, and real-world implementations that turn governance from a static document into an operational advantage that accelerates trust, compliance, and AI readiness.
Insights
5 common problems with unstructured data
Unstructured data is no longer just a storage problem - it is a financial, architectural, and compliance risk that can quietly undermine your AI strategy. In this article, we break down the five systemic issues that prevent organizations from turning chaotic archives into governed, high-value intelligence.
Insights
Structured vs unstructured data: key differences
Structured and unstructured data are no longer just technical categories - they define how much of your enterprise knowledge is usable, governed, and AI-ready. In this guide, we break down the real differences, risks, and architectural implications, and explain how to turn hidden “dark data” into a strategic asset instead of a compliance liability.
Collibra
Unstructured data cataloging for AI and compliance
We’ve talked about discovering and classifying unstructured data, now it’s time to catalog it to make sure it’s governed (and used) properly.
Collibra
Collibra consulting: What to expect & how to choose a firm
Time to hire Collibra consultants? Here’s when to do it, what to look out for, and what to expect for your business and data governance needs.
Collibra
How to choose a Collibra Partner: resellers, service partners & tiers explained
Choosing a Collibra service partner? Get our guide on DIY vs. pro, partner tiers, and the 10 essential questions to ask before you decide.
Data Quality
How to build a data quality strategy
Build data quality strategies for accurate, consistent, and complete data. Learn key processes, techniques, and tools for data quality.
Data Governance
How to build a successful data governance program
Build a successful data governance program that drives revenue. Learn the steps to setup a framework that balances stewardship and data management.
Collibra
Unstructured data classification – how to do it at scale
Discovering unstructured data is just the first step in managing it. The next is proper classification – here’s how to do it at scale.
Data Governance
Data Governance vs data stewardship
Understand how data governance and data stewardship differ in practice and why clearly separating strategy from execution is the key to turning policies into trusted, operational data at scale.
Data Governance
Data governance vs data quality: What’s the difference?
Discover how data quality and data governance play distinct but complementary roles and why mastering both is essential to building trusted data, reliable AI, and confident executive decisions.
Data Governance
Data governance roadmap
Learn how to turn a data governance strategy into real execution with a practical roadmap that delivers measurable value, supports AI readiness, and evolves with your business instead of collecting dust.
Data Governance
The 6 benefits of data governance
Read this article to see how data governance moves beyond compliance to deliver measurable ROI, eliminating data distrust, reducing costs, strengthening security, and enabling faster, smarter decisions across the business.
Data Governance
Top data governance trends: The future of data in 2026
Discover how data governance in 2026 becomes the invisible system that stops runaway AI, enforces compliance in real time, and lets organizations innovate safely at machine speed.
Data Governance
Data governance framework. Best practices & examples
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.
Data Governance
Building a data governance strategy
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 Quality
Data observability vs data quality: key differences
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.
Data Governance
Data governance policy
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.
Collibra
How to build custom data quality checks
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.
Data Catalog
Data cataloging process
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.
Data Governance
The 7 data governance pillars
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.
Data Governance
Data governance roles and responsibilities
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.
Data Quality
10 Best Data Quality Tools for 2026 – A Comprehensive Guide
This 2026 guide breaks down the best data quality tools, what to look for, and how to choose the right platform for your data ecosystem.
Collibra
Unstructured data discovery with Collibra and Ohalo Data X-Ray
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.
Data Quality
Data quality automation
this article shows why automated data quality is the difference between a minor error and a business-ending disaster, and how to implement it in practice.
Collibra
A proven data governance Collibra implementation plan
A practical, experience-driven Collibra implementation blueprint that cuts through theory and shows how enterprise data governance succeeds or fails in real life.
Case Study
Case Study: Implementing Data Shopping for a global retailer
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.
Collibra
Collibra Data Governance: features, overview, and case studies
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.
Collibra
What is Collibra Edge? A 2026 Explainer
Explore what Collibra Edge really is, how it extends governance to distributed and edge environments, and why it matters for organizations that need consistent data quality, control, and policy enforcement beyond the core data stack.
Collibra
The definitive guide to Collibra Data Lineage
Learn how effective Collibra data lineage transforms opaque data flows into clear, trusted paths, enabling faster impact analysis, reliable reporting, and greater confidence in every decision that relies on your data.
Case Study
Case Study: Discovering, classifying and cataloging unstructured data for a European bank
Get insights from a real enterprise case where unstructured data hidden in PDFs, emails, and legal files was automatically discovered, classified, and cataloged into Collibra, giving the bank full visibility of sensitive information, reducing compliance risk, and turning previously invisible data into governed, searchable assets.
Case Study
Case Study: Optimizing Collibra licenses for a global energy company
See how a global energy company significantly cut Collibra platform costs by right-sizing user roles and optimizing license usage, without disrupting critical governance workflows or operational continuity.
Collibra
The ultimate guide to Collibra Data Catalog
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.
Collibra
5 Steps to Operationalize AI Governance With Collibra
Unpack how Collibra turns AI governance from abstract policy into enforceable guardrails, so your AI can move fast without drifting into compliance, ethical, or operational risk.
Data Quality
Data quality vs data integrity
This article breaks down two often confused concepts of data quality and data integrity, explaining how they differ, why both matter, and how aligning them dramatically improves trust in your data and outcomes.
Data Quality
Data quality for manufacturing
Discover how poor data quality quietly drains manufacturing performance and costs millions, and learn practical strategies to fix data issues that directly improve efficiency, product quality, and operational decisions.
Data Quality
How to improve data quality in retail
Learn actionable strategies retailers are using to fix data quality at the source, eliminate costly errors, and turn accurate data into faster decisions, better customer experiences, and higher margins.
Data Quality
Data quality testing cheat sheet: 10 effective data quality checks
This article explains the essential data quality checks every team needs to implement, why they matter, and how they turn unreliable data into a dependable foundation for analytics, reporting, and AI.
Data Quality
Build a data quality framework for business value
This article presents a practical framework for improving data quality across your organization, showing how structured checks, roles, and processes turn unreliable data into a trusted foundation for better decisions and analytics.
Career
How to become a Collibra Ranger: certification, salary, and career path
Get an inside look at what it takes to earn the elite Collibra Ranger certification, how it can accelerate your data governance career, and the real-world skills and opportunities that come with this advanced expertise.
Collibra
What is a Collibra Ranger
Who do you see when you think of a ranger? If it’s a keeper of a national park, you’re not far off when it comes to the world of data…
Data Quality
Create a data quality scorecard: improve your data quality score
Turn vague data quality concerns into clear, actionable signals by using a data quality scorecard that shows where trust is earned, where it breaks, and what to fix first.
Data Quality
Data quality best practices
Unlock dependable data by applying data quality best practices that prevent errors at the source, streamline validation, and ensure your analytics and decisions rest on trustworthy information.
Data Quality
How to build a data quality dashboard to ensure data accuracy
Visualize your data health with a data quality dashboard that turns messy signals into clear insights, helping teams spot issues fast and act confidently on trusted information.
Data Quality
How to choose a data quality platform?
Choose the right data quality platform by learning what capabilities truly matter, how to match tools to your use cases, and how the right choice can save time, reduce risk, and boost trust in your data.
Data Quality
The ultimate guide to data quality assurance
Ensure your data is always reliable by applying proven quality assurance practices that catch issues early, enforce standards across systems, and make trusted data the default for every decision and process.
Collibra
Collibra Data Quality and Observability: What Is It, and Why Should You Care?
Uncover how Collibra transforms data quality from endless firefighting into automated trust, so teams stop fixing spreadsheets and start making decisions that actually move the business forward.
Data Quality
What is data quality?
Understand what data quality really means, how it impacts every part of your business, and why getting it right is foundational to reliable analytics, AI, and operational excellence.
Collibra
How to Pitch and Implement Collibra Data Marketplace
Imagine unlocking your enterprise data like an internal data store, where every team can instantly find trusted, certified datasets. Collibra turns this into reality and accelerates self-service analytics.
Data Quality
The definitive guide to data quality improvement
Improve your data at the source with practical strategies that reduce errors, boost reliability, and make your data ready for analytics, governance, and AI with measurable results.
Data Quality
A practical guide to Data Quality Assessment (DQA)
Evaluate your data with a systematic quality assessment that pinpoints the biggest issues, quantifies trust gaps, and gives you a clear roadmap to elevate data reliability and decision-making confidence.
Data Quality
10 common data quality issues (and how to fix them for good)
Identify the most common data quality issues that silently derail analytics, inflate costs, and erode trust, so you can fix the right problems before they break critical business decisions.
Data Quality
The ultimate guide to 8 data quality dimensions with examples
Explore the core dimensions of data quality and learn how assessing attributes like accuracy, completeness, and consistency can transform your data from a liability into a reliable strategic asset.
Collibra
Common pitfalls in Collibra Workflows implementation
Collibra workflows can unlock massive value or quietly fail. This article breaks down the most common pitfalls teams hit and how to design workflows that actually get adopted and deliver results.
Data Catalog
Augmented Data Catalogs – What Does “Augmented” Really Mean
Explore how the next evolution of data catalogs breaks past manual discovery to deliver smarter, faster, and more trusted data insights across your organization
Data Catalog
Data Catalog vs Data Lake: A Comprehensive Comparison
A data lake stores everything, but a data catalog explains what it actually means. This article shows why you need both, and what breaks when you rely on one without the other.
Case Study
Case Study: Building a Collibra data marketplace for a global life sciences company
See how a global organization built a Collibra-powered Data Marketplace that transformed self-service data access, reduced IT bottlenecks, and empowered business teams with certified datasets they can trust and use independently.
Data Catalog
Evaluating Data Catalog Requirements – a Guide for Enterprise Teams
Discover the must-have features that separate passive data catalogs from intelligent ones, so you build a system that actually drives trust, discovery, and usable insights instead of collecting dust.
Career
Career Path as a Collibra Specialist in Data Governance
Learn what a career as a Collibra Specialist involves - from entry-level roles to leadership paths, key skills, and real industry demand -so you can decide if it’s the right data governance trajectory for your future.
Data Catalog
Data Inventory vs Data Catalog – Which One Do You Need?
A data inventory tells you what data you have, but a data catalog explains how it’s used, trusted, and governed. This article shows why that distinction defines whether data becomes a risk or a real business asset.
Data Catalog
Data Catalog Pricing: How Much Does It Really Cost?
Navigate the hidden cost-drivers of data catalog pricing. This article breaks down what you actually pay for, what you’re better off budgeting for, and how to avoid surprises that drain value before you see any.
Data Catalog
Data catalog vs metadata management: key differences and common goals
A data catalog is the user-facing window into your data, while metadata management is the engine that keeps it accurate, governed, and trustworthy. This article explains why separating the two is a mistake and how they work together in practice.
Data Catalog
Machine learning data catalog: A 2026 in-depth look
This article explains what machine learning data catalogs are how they differ from traditional catalogs by organizing and tracking data, features, versions, lineage, and collaboration across ML lifecycles.
Data Catalog
15 Best data catalog tools for enterprise: A guide for 2026
Explore the current landscape of data catalog tools, what features truly matter in 2026, and how choosing the right one can turn a scattered data estate into a searchable, governed, and actionable asset for your organization.
Data Catalog
Data catalog vs. data warehouse. Which do you need?
A data warehouse holds your data, but a data catalog makes it discoverable, meaningful, and trusted. This article explains how confusing the two can leave analytics blind and governance incomplete.
Data Catalog
Enterprise Data Catalog: The Complete Guide for 2026
Learn what sets an enterprise-grade data catalog apart from basic ones and why investing in the right catalog architecture is key to scaling discovery, governance, and trust across all of your organization’s data assets.
Data Catalog
Data Catalog vs Data Dictionary: Understanding Their Roles in Data Governance
Discover why a data catalog is more than just a glorified dictionary and how it provides the context, governance, and discoverability that a simple list of definitions can’t deliver for modern data teams.
Data Catalog
Data Catalog vs Data Lineage: Tools for Complete Data Intelligence
Understand the difference between a data catalog and data lineage, why both are critical to data trust, and how combining them gives you visibility and context across your entire data lifecycle.
Data Catalog
How to Build a Data Catalog: A Step-by-Step Guide
This article breaks down how to build a data catalog that actually gets used, turning scattered metadata into a practical foundation for data discovery, governance, and everyday decision-making.
Case Study
Case Study: Strengthening AI Governance in a global bank
Learn how a leading global bank centralized its AI model governance with a scalable inventory platform, boosting compliance, transparency, and lifecycle management while overcoming fragmented documentation and regulatory risk.
Data Catalog
Business Glossary vs Data Catalog: understanding the key differences and benefits
Understand the difference between a business glossary and a data catalog, and why both are essential. One gives shared definitions, while the other makes data discoverable, trusted, and actionable across your organization.
Data Catalog
Data Catalog: Best Practices and Tips for Implementation and Maintenance
Learn the essential practices that turn a data catalog from shelfware into a living system that drives discovery, governance, and reliable decision-making across your organization.
Data Governance
Data Governance: Why It’s Critical and How to Get Started
Get Murdio's founder perspective on data governance as Łukasz Banaszewski shares why it became a cornerstone of Murdio’s work and how organizations can move from theory to action when getting started.
Data Catalog
Data Catalog Benefits: A Complete Guide for 2026
Most organizations already have the data they need to make better decisions. This article shows how a data catalog is often the missing layer that turns hidden, unused data into a trusted asset the business can actually act on.
Case Study
Case Study: How an energy giant transformed its Collibra implementation with a Technical Product Owner
Follow how introducing clear technical ownership turned a stalled governance program into a predictable, scalable delivery engine, unlocking faster execution, better prioritization, and real business impact from Collibra.
Case Study
Case study: Management and cataloging sensitive critical data elements in a Swiss bank
Explore how a Swiss private bank automated the cataloging and governance of its most sensitive data across 100+ applications, meeting strict regulatory requirements, improving data visibility, and turning an underused Collibra instance into a core compliance asset.
Data Catalog
What is a data catalog? Metadata, functions and use cases
A data catalog is not just a list of datasets. This complete, end-to-end guide to data catalogs explains what they are, how metadata works, and how real organizations use them to move from data chaos to clarity, trust, and everyday impact.
Case Study
Case Study: Collibra Implementation Team for an international retail chain
See how embedding a dedicated Collibra implementation team helped an international retail chain optimize its governance rollout, reducing complexity, increasing adoption, and turning a fragmented environment into an efficient, scalable platform
Case Study
Case study: Custom Collibra SAP lineage implementation
Discover how custom Collibra-SAP lineage integration gave an enterprise automated, end-to-end visibility into SAP data flows, eliminating manual effort, enhancing impact analysis, and strengthening governance confidence across complex systems.
Case Study
Case study: Collibra Technical Implementation Team for a DACH retailer
Uncover how a tailored Collibra technical implementation team turned a complex, multi-instance environment at a DACH retailer into a streamlined, cost-efficient governance platform with higher adoption and measurable operational value.