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DOUBTS regarding Data Virtualization concept

  • 1.  DOUBTS regarding Data Virtualization concept

    Posted Mon September 19, 2022 06:54 AM
    Hello All,

    Could you please help me resolving few doubts on DATA VIRTULIZATION in IBM Cloud pak-

    DOUBT 1: On the Virtualized data can we do profiling(generate data quality score) ?
    DOUBT 2:
    Can you give some use cases whether this service is useful?


    Thanks & Regards
    Rajni





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    RAJNI HARYANI
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    #CloudPakforDataGroup


  • 2.  RE: DOUBTS regarding Data Virtualization concept

    Posted Thu September 29, 2022 07:54 PM
    Hi Rajni,

    1. You couldn't generate data quality score inside Data Virtualization service. But you could assign virtualized data to an analytics project on Virtualized data page. And then you could go to the project and run Metadata Import and Metadata Enrichment against the virtualized data asset. You would be able to see the data quality on the details of virtualized data asset.

    2. Here are some key value propositions of Data Virtualization service:
    • Reduce data copies and movement, avoid production data being replicated everywhere
    • Query multiple data sources as one single database to simply integrate data across hybrid and multiple clouds
    • Deeply integration with Watson Knowledge Catalog to protect sensitive data
    • Enable self-service for data by leveraging business glossary
    • Avoid ETL, faster time to value
    • Smart caches to accelerate analytics queries and reduce overheads to production system
    Data Virtualization services can be useful in the following common user cases:
    • EDW prototyping and migration (mergers/acquisitions)
    • Virtualization with Big Data (Hadoop, NoSQL, and Data Science)
    • EDW augmentation (offload workload)
    • On-demand Virtual Data Marts saves on cost of standing up EDW
    • Data discovery for "what if" scenarios across hybrid platforms
    • Data Caching of combined data for frequently accessed data
    • Combine MDM with IoT for Systems of Insight (IT/OT)
    • Data integration preparation tool to complement ETL
    • Master data hub extension to enrich 360 View (e.g. multi-channel CRM)


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    JUN LIU
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