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Five Important Considerations When Cataloging Your Data

Lakshmi Randall
Intel Data Center GPU codenamed Crescent Island architectural slide showcasing Xe3P AI optimized GPU IP, up to 480GB LPDDR5x memory capacity, and a 350W air-cooled PCIe form factor.

Intel’s Crescent Island GPU targets AI inference economics by prioritizing massive LPDDR5x memory capacity over costly HBM architectures within a practical 350W air-cooled design.

Here are five things to consider when thinking about cataloging your data:

  1. Clearly define the objectives of your data catalog(s) such as:
    • Archiving
    • Discovery of data in support of information management and analytics initiatives
    • Digitalization
    • Understanding data lineage
    • Building knowledge and increasing data stewardship
  2. Mapping of technical metadata to business metadata in order to facilitate understanding of data
  3. Control access to the Data Catalog. A good data cataloging product should be able to support multiple personas and protect sensitive information.
  4. If you are enabling access to data assets through data cataloging process, ensure the information is exposed at the appropriate granularity level and sufficient metadata is provided along with data.
  5. Metadata generated by the data cataloging product should be accessible and provide integration with enterprise metadata product and other products as appropriate.
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