Articles
What questions should content managers consider when deciding if data lakes are the right option for their organization?
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If data is the language upon which our modern society is built, then metadata is the grammar, the construction of its meaning.
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For AI and machine learning to truly support and improve customer service, we must feed them good quality data.
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Data makes everything easier. Conducting a systematic data assessment gives insight into where an organization stands in managing its information.
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The future of information management architecture is where the backend repository is separate from the user interface.
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Effective governance is one of the major factors determining the ultimate success or failure of a DAM initiative.
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Microsoft's Project Cortex sounds complicated, but the foundation for all this complexity is pretty humble: metadata. Here's how and where metadata fits in.
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Search managers developing their existing application or planning a new application should start with the user interface (UI) and work backwards.
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The best way to plan for change is to apply an effective layer of governance to your DAM and other content programs.
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We want machines/robots to learn and do more, but we must provide them with good, quality data in order for them to do that.
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The current artificial intelligence image recognition tools used in DAM systems are comparable to a pair of eyes disconnected from the brain.
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DAM is more than just a parking lot where customer experience assets sit.
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Not properly capturing and sharing information at the point of creation is a hard problem to fix down the line.
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Make metadata meaningful to you, your users and your organization by managing it well.
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