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Why Your Master Data Management Needs Data Governance

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Master Data Management systems (MDM) play an important role in harmonizing data assets across large and midsize enterprises. However, to get optimal value from your organization’s data, you need to apply the discipline of data governance to your MDM. Nevertheless, MDM is not a silver bullet for data quality.

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Following the Roadmap to Better Data Governance

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Data governance is no trivial undertaking. When executed correctly, data governance transitions businesses from guesswork to data-informed strategies. For those who follow the right roadmap on their data governance journey, the payoff can be enormous.

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Unraveling the Threads: Data Fabric vs Data Mesh for Modern Enterprises

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Both architectures tackle significant data management challenges such as integrating disparate data sources, improving data accessibility, automating management processes, and ensuring data governance and security. Problems it solves Data fabric addresses key data management and use challenges.

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How to Build a Meshy Data Fabric (With a Data Catalog!)

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This white paper makes this information actionable with a methodology, so you can learn how to implement a meshy fabric with your data catalog. For the full story, download the white paper here ! to an external, compliance-focused perspective (“How do we ensure analysts use private data legally?”).

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Mainframe Data: Empowering Democratized Cloud Analytics

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This has compelled business users to expand their knowledge of data management and enhance their analytics skills. It has also highlighted the need to democratize data access and management, offering more open access to data that was previously unavailable. The movement of data also grows more complex with data democratization.

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The Human-Centric CDO: 3 Key Takeaways from the Gartner Data & Analytics Summit 2023 in London

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D&A leaders from around the world gathered to discuss and find ways to overcome the latest challenges through strategies and innovations backed by data, analytics, and data science. The observations comprised a mix of classic (the power of people, data quality ), recent (architectures such as fabric and mesh ), and emerging (AI).

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Data Mesh vs. Data Fabric: A Love Story

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But how do you identify the best data, and best practices for using it? Metadata is the key to fueling data intelligence use cases across the board, including data search & discovery and data governance. In fact, data intelligence technologies support building a data fabric and realizing a data mesh.