How to Implement Data Catalog and Metadata Management in 2025

🚀 The future of data stewardship with AI agents In the third article of our four-part series, Maria C Villar, Mike Alvarez, Beth Hiatt, and Christine Legner examine how the Digital Data Steward (DDS), powered by AI Agents, augments four critical areas of data governance: ✅ Data Quality ✅ Metadata Management ✅ Master Data ✅ Data Retention From anomaly detection to metadata orchestration and retention compliance, discover how AI agents are shifting from simple automation to cross-agent orchestration that predicts, alerts, corrects — and empowers human stewards to focus on higher-value work. 👉 Read the full article here: https://hubs.ly/Q03G8J1p0

A biotech firm faced fragmented data across siloed systems, delaying critical reporting and analytics. SingleStone’s AI-driven solution built a unified enterprise domain model and modernized their data warehouse, slashing reporting delays and enabling real-time insights. This transformation boosted decision-making speed, operational efficiency, and innovation, positioning the firm for growth. By integrating AI, SingleStone turned data chaos into a strategic asset. The result? Faster, smarter analytics that drive competitive advantage. How could unified data transform your organization’s efficiency? https://loom.ly/r9X7_h4

💡 AI and open-source are transforming enterprise data platforms in 2025 and businesses that adapt early are gaining a real competitive edge. At PaperTrail, we see this trend reflected every day: companies need flexible, intelligent, and unified data solutions to unlock the full value of their information. Here are three key takeaways from the recent Forbes article, “AI And Open Source Redefine Enterprise Data Platforms In 2025”: ✅ Scalable and Adaptive Platforms: Modern enterprise data platforms leverage AI and open-source technology to scale quickly and adapt to evolving business needs, reducing reliance on rigid legacy systems. ✅ Cost Efficiency and Operational Agility: By integrating AI-driven automation and open-source tools, businesses can process and structure data more efficiently 📈, cutting operational costs 💰 while improving decision-making speed. ✅ Data as a Strategic Asset: Structured, searchable and enriched data becomes a cornerstone for innovation, powering analytics, AI agents, and better collaboration across departments 🤝. PaperTrail is at the forefront of this shift, transforming unstructured documents into a unified, actionable knowledge base. #papertrailgr #fromdatatoknowledge #AI #datamanagement https://lnkd.in/dCUBFR6V

The role of the data steward is being redefined in the age of Agentic AI. Back in my Reltio days, I had the opportunity to walk in the shoes of data stewards through a day-in-the-life program, seeing firsthand the workflows involved in onboarding, reviewing, and cleaning data to ensure it was fit for use. In regulated industries, especially, these tasks are critical but also manual, error-prone, and labor-intensive. What was once a human-heavy responsibility, ensuring data quality, managing metadata, overseeing master data, and enforcing retention, can now be amplified through AI agents that act automatically, continuously, and at scale. This CDO Magazine piece highlights how embedding agentic automation into stewardship shifts us from reactive governance to proactive, real-time assurance: 👉 Data quality checks become autonomous 👉 Metadata is enriched and validated as data lands 👉 Retention and lifecycle policies are applied consistently, without waiting on human intervention For me, it signals a broader shift: trust in data can no longer be after-the-fact. It must be built-in, automated, and always-on because that’s what modern AI and business workflows demand. 📖 Worth a read: Digital Data Steward: Leveraging Agentic AI for Data Quality, Metadata, Master Data Management, and Data Retention by Maria C Villar Mike Alvarez and others. https://lnkd.in/g3ckVBth #agenticworkflows #dataobservability #dataquality #datamanagement

Organizations are modernizing data management with IBM watsonx.data, a hybrid and governed lakehouse platform that unifies data across domains. The Data Product Hub serves as a centralized marketplace where users can discover, subscribe to, and receive data products directly into their lakehouses, regardless of where the data originates. This simplifies delivery, accelerates insights, and supports better decision-making. Governed access and analysis are enabled through the watsonx.data console, making data sharing seamless for both providers and consumers. #IBMwatsonx #DataLakehouse #DataProducts #AI #DataManagement #HybridCloud Read more below: https://lnkd.in/gMdVUwpT

New Article: Open Data Fabric – Rethinking Data Architecture for AI at Scale Enterprises are racing to put AI agents into production. But too many are finding that what works in a demo fails in the real world. The issue isn’t the agents – it’s the data architecture they’re forced to run on. Today’s “modern data stack” was built for humans and dashboards. AI agents need something different: ✅ Real-time access to all enterprise data (not batch refreshes) ✅ Rich business context to prevent hallucinations ✅ A collaborative, iterative workflow that supports self-service at machine speed This is where the Open Data Fabric comes in. Instead of forcing everything into a single vendor’s stack, it provides: - Unified data access across distributed systems without duplication - Contextual intelligence that grounds AI in business meaning - Collaborative self-service where humans and agents refine, share, and trust results Read the full breakdown from CEO Prat Moghe on why the right data foundation is the key to making enterprise AI actually work 👇 👉 https://lnkd.in/eCZNeBMM

Contributed to recently published ISG Software Research market perspective highlighting how enterprise success in the AI era hinges on an AI-ready data foundation, requiring not just new approaches to data management and governance but also a rethinking of how software providers align data and AI. It further explores Pentaho's pivot from legacy to AI-native in the data economy. Read the full perspective here: https://lnkd.in/gJd62DR6 #datagovernance #dataintelligence #Analytics #AI #GenAI #datamanagement #datastrategy #datafoundation #isg #isgsoftwareresearch #isgresearch

Data migration is no longer just a “lift and shift” for me—it’s a business transformation. As I highlighted in Intelligent CIO APAC when I move data, I focus on: • Gaining insight into what you have • Migrating only what delivers value • Automating with intelligence at scale • Embedding governance and readiness from Day One The result? My migrations fuel AI, strengthen compliance, reduce costs, and set the foundation for long-term business growth. Read full article here: https://bit.ly/45DoYxq DataMigration #BusinessTransformation #DataManagement #UnstructuredData #AI

The Most Underrated Data Tool in Your Stack: The Data Dictionary. It’s no longer just a documentation exercise. In 2025, a well-maintained data dictionary does a lot more: - Enforces governance and compliance - Powers AI and metadata automation - Speeds up onboarding - Improves data quality - Enables business users to explore data confidently If you're not treating your data dictionary like a strategic asset, you’re leaving value on the table. 📖 Learn how ....you don't even need to drop a comment ;) 5 Use Cases and 5 Critical Best Practices https://lnkd.in/gxx6kNCm Collate #DataDictionary #DataGovernance #Metadata #DataOps

This evolution underscores a critical moment for AI strategy: designing systems that are not only powerful but also transparent, flexible, and scalable. As enterprises increasingly integrate these advanced architectures, the collaboration between AI and open-source tools is reshaping the future of data platforms. #AI #OpenSource #EnterpriseAI #DataPlatforms #DigitalTransformation