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Governing the ML lifecycle at scale, Part 3: Setting up data governance at scale

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This post dives deep into how to set up data governance at scale using Amazon DataZone for the data mesh. The data mesh is a modern approach to data management that decentralizes data ownership and treats data as a product.

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Mastering healthcare data governance with data lineage

IBM Journey to AI blog

The healthcare industry faces arguably the highest stakes when it comes to data governance. For starters, healthcare organizations constantly encounter vast (and ever-increasing) amounts of highly regulated personal data. healthcare, managing the accuracy, quality and integrity of data is the focus of data governance.

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Why Your Data Governance Strategy is Failing

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What is data governance and how do you measure success? Data governance is a system for answering core questions about data. It begins with establishing key parameters: What is data, who can use it, how can they use it, and why? Why is your data governance strategy failing?

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Understanding Data Governance

IBM Journey to AI blog

If you’re in charge of managing data at your organization, you know how important it is to have a system in place for ensuring that your data is accurate, up-to-date, and secure. That’s where data governance comes in. What exactly is data governance and why is it so important?

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Solving Complex Telecom Challenges with Data Governance and Location Analytics

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For instance, telcos are early adopters of location intelligence – spatial analytics has been helping telecommunications firms by adding rich location-based context to their existing data sets for years. Despite that fact, valuable data often remains locked up in various silos across the organization.

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9 data governance strategies that will unlock the potential of your business data

IBM Journey to AI blog

Everything is data—digital messages, emails, customer information, contracts, presentations, sensor data—virtually anything humans interact with can be converted into data, analyzed for insights or transformed into a product. Managing this level of oversight requires adept handling of large volumes of data.

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Data virtualization unifies data for seamless AI and analytics

IBM Journey to AI blog

Despite heavy investments in databases and technology, many companies struggle to extract further value from their data. Data virtualization bridges this gap, allowing organizations to use their existing data sources with flexibility and efficiency for AI and analytics initiatives.