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  • 1
    ISBN: 9780738459028
    Language: English
    Pages: 1 online resource (108 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    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.
    Note: Online resource; Title from title page (viewed August 11, 2020) , Mode of access: World Wide Web.
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  • 2
    Language: English
    Pages: 1 online resource (64 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Advancing the science of medicine by targeting a disease more precisely with treatment specific to each patient relies on access to that patient's genomics information and the ability to process massive amounts of genomics data quickly. Although genomics data is becoming a critical source for precision medicine, it is expected to create an expanding data ecosystem. Therefore, hospitals, genome centers, medical research centers, and other clinical institutes need to explore new methods of storing, accessing, securing, managing, sharing, and analyzing significant amounts of data. Healthcare and life sciences organizations that are running data-intensive genomics workloads on an IT infrastructure that lacks scalability, flexibility, performance, management, and cognitive capabilities also need to modernize and transform their infrastructure to support current and future requirements. IBM® offers an integrated solution for genomics that is based on composable infrastructure. This solution enables administrators to build an IT environment in a way that disaggregates the underlying compute, storage, and network resources. Such a composable building block based solution for genomics addresses the most complex data management aspect and allows organizations to store, access, manage, and share huge volumes of genome sequencing data. IBM Spectrum™ Scale is software-defined storage that is used to manage storage and provide massive scale, a global namespace, and high-performance data access with many enterprise features. IBM Spectrum Scale™ is used in clustered environments, provides unified access to data via file protocols (POSIX, NFS, and SMB) and object protocols (Swift and S3), and supports analytic workloads via HDFS connectors. Deploying IBM Spectrum Scale and IBM Elastic Storage™ Server (IBM ESS) as a composable storage building block in a Genomics Next Generation Sequencing deployment offers key benefits of performance, scalability, analytics, and collaboration via multiple protocols. This IBM Redpaper™ publication describes a composable solution with detailed architecture definitions for storage, compute, and networking services for genomics next generation sequencing that enable solution architects to benefit from tried-and-tested deployments, to quickly plan and design an end-to-end infrastructure deployment. The preferred practices and fully tested recommendations described in this paper are derived from running GATK Best Practices work flow...
    Note: Online resource; Title from title page (viewed April 25, 2018)
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