Cataloging Unstructured Data in IBM Watson Knowledge Catalog with IBM Spectrum Discover

An IBM Redpaper publication

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Published on August 11, 2020

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ISBN-10: 073845902x
ISBN-13: 9780738459028
IBM Form #: REDP-5603-00


Authors: Joseph Dain, Abeer Selim, Anil Patil, Christopher Vollmar, Flavio de Rezende, PhD, Frank Greco, Frank N. Lee, PhD, Isom Crawford Jr., PhD, Ivaylo B. Bozhinov, Joanna Wong, PhD, Joshua Blumert and Larry Coyne

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    Abstract

    This IBM® Redpaper publication explains how IBM Spectrum® Discover integrates with the IBM Watson® Knowledge Catalog (WKC) component of IBM Cloud® Pak for Data (IBM CP4D) to make the enriched catalog content in IBM Spectrum Discover along with the associated data available in WKC and IBM CP4D. From an end-to-end IBM solution point of view, IBM CP4D and WKC provide state-of-the-art data governance, collaboration, and artificial intelligence (AI) and analytics tools, and IBM Spectrum Discover complements these features by adding support for unstructured data on large-scale file and object storage systems on premises and in the cloud.

    Many organizations face challenges to manage unstructured data. Some challenges that companies face include:

    • Pinpointing and activating relevant data for large-scale analytics, machine learning (ML) and deep learning (DL) workloads.
    • Lacking the fine-grained visibility that is needed to map data to business priorities.
    • Removing redundant, obsolete, and trivial (ROT) data and identifying data that can be moved to a lower-cost storage tier.
    • Identifying and classifying sensitive data as it relates to various compliance mandates, such as the General Data Privacy Regulation (GDPR), Payment Card Industry Data Security Standards (PCI-DSS), and the Health Information Portability and Accountability Act (HIPAA).

    This paper describes how IBM Spectrum Discover provides seamless integration of data in IBM Storage with IBM Watson Knowledge Catalog (WKC). Features include:

    • Event-based cataloging and tagging of unstructured data across the enterprise.
    • Automatically inspecting and classifying over 1000 unstructured data types, including genomics and imaging specific file formats.
    • Automatically registering assets with WKC based on IBM Spectrum Discover search and filter criteria, and by using assets in IBM CP4D.
    • Enforcing data governance policies in WKC in IBM CP4D based on insights from IBM Spectrum Discover, and using assets in IBM CP4D.

    Several in-depth use cases are used that show examples of healthcare, life sciences, and financial services.

    IBM Spectrum Discover integration with WKC enables storage administrators, data stewards, and data scientists to efficiently manage, classify, and gain insights from massive amounts of data. The integration improves storage economics, helps mitigate risk, and accelerates large-scale analytics to create competitive advantage and speed critical research.

    Table of Contents

    Chapter 1. IBM Spectrum Discover overview

    Chapter 2. IBM Watson Knowledge Catalog and IBM Cloud Pak for Data overview

    Chapter 3. IBM Spectrum Discover integration with IBM Watson Knowledge Catalog architecture and benefits

    Chapter 4. Curating unstructured data for IBM Watson Knowledge Catalog with IBM Spectrum Discover

    Chapter 5. Healthcare and life sciences use cases

    Chapter 6. Financial services use case: Personally Identifiable Information detection and data governance

    Chapter 7. Conclusion

     

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