Cataloging Unstructured Data In Ibm Watson Knowledge Catalog With Ibm Spectrum Discover
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Cataloging Unstructured Data In Ibm Watson Knowledge Catalog With Ibm Spectrum Discover
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Author : Joseph Dain
language : en
Publisher: IBM Redbooks
Release Date : 2020-08-11
Cataloging Unstructured Data In Ibm Watson Knowledge Catalog With Ibm Spectrum Discover written by Joseph Dain and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-11 with Computers categories.
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.
Cataloging Unstructured Data In Ibm Watson Knowledge Catalog With Ibm Spectrum Discover
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Author : Joseph Dain
language : en
Publisher:
Release Date : 2020
Cataloging Unstructured Data In Ibm Watson Knowledge Catalog With Ibm Spectrum Discover written by Joseph Dain and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Database management categories.
Ibm Spectrum Discover Metadata Management For Deep Insight Of Unstructured Storage
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Author : Joseph Dain
language : en
Publisher: IBM Redbooks
Release Date : 2019-10-01
Ibm Spectrum Discover Metadata Management For Deep Insight Of Unstructured Storage written by Joseph Dain and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-01 with Computers categories.
This IBM® Redpaper publication provides a comprehensive overview of the IBM Spectrum® Discover metadata management software platform. We give a detailed explanation of how the product creates, collects, and analyzes metadata. Several in-depth use cases are used that show examples of analytics, governance, and optimization. We also provide step-by-step information to install and set up the IBM Spectrum Discover trial environment. More than 80% of all data that is collected by organizations is not in a standard relational database. Instead, it is trapped in unstructured documents, social media posts, machine logs, and so on. Many organizations face significant challenges to manage this deluge of unstructured data such as: Pinpointing and activating relevant data for large-scale analytics Lacking the fine-grained visibility that is needed to map data to business priorities Removing redundant, obsolete, and trivial (ROT) data Identifying and classifying sensitive data IBM Spectrum Discover is a modern metadata management software that provides data insight for petabyte-scale file and Object Storage, storage on premises, and in the cloud. This software enables organizations to make better business decisions and gain and maintain a competitive advantage. IBM Spectrum Discover provides a rich metadata layer that enables storage administrators, data stewards, and data scientists to efficiently manage, classify, and gain insights from massive amounts of unstructured data. It improves storage economics, helps mitigate risk, and accelerates large-scale analytics to create competitive advantage and speed critical research.
Making Data Smarter With Ibm Spectrum Discover Practical Ai Solutions
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Author : Ivaylo B. Bozhinov
language : en
Publisher: IBM Redbooks
Release Date : 2020-10-19
Making Data Smarter With Ibm Spectrum Discover Practical Ai Solutions written by Ivaylo B. Bozhinov and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-19 with Computers categories.
More than 80% of all data that is collected by organizations is not in a standard relational database. Instead, it is trapped in unstructured documents, social media posts, machine logs, and so on. Many organizations face significant challenges to manage this deluge of unstructured data, such as the following examples: Pinpointing and activating relevant data for large-scale analytics Lacking the fine-grained visibility that is needed to map data to business priorities Removing redundant, obsolete, and trivial (ROT) data Identifying and classifying sensitive data IBM® Spectrum Discover is a modern metadata management software that provides data insight for petabyte-scale file and Object Storage, storage on-premises, and in the cloud. This software enables organizations to make better business decisions and gain and maintain a competitive advantage. IBM Spectrum® Discover provides a rich metadata layer that enables storage administrators, data stewards, and data scientists to efficiently manage, classify, and gain insights from massive amounts of unstructured data. It improves storage economics, helps mitigate risk, and accelerates large-scale analytics to create competitive advantage and speed critical research. This IBM Redbooks® publication presents several use cases that are focused on artificial intelligence (AI) solutions with IBM Spectrum Discover. This book helps storage administrators and technical specialists plan and implement AI solutions by using IBM Spectrum Discover and several other IBM Storage products.
Ibm Spectrum Discover
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Author : Joe Dain
language : en
Publisher:
Release Date : 2019
Ibm Spectrum Discover written by Joe Dain and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Database management categories.
Ibm Power Systems Enterprise Ai Solutions
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Author : Scott Vetter
language : en
Publisher: IBM Redbooks
Release Date : 2019-09-25
Ibm Power Systems Enterprise Ai Solutions written by Scott Vetter and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-25 with Computers categories.
This IBM® Redpaper publication helps the line of business (LOB), data science, and information technology (IT) teams develop an information architecture (IA) for their enterprise artificial intelligence (AI) environment. It describes the challenges that are faced by the three roles when creating and deploying enterprise AI solutions, and how they can collaborate for best results. This publication also highlights the capabilities of the IBM Cognitive Systems and AI solutions: IBM Watson® Machine Learning Community Edition IBM Watson Machine Learning Accelerator (WMLA) IBM PowerAI Vision IBM Watson Machine Learning IBM Watson Studio Local IBM Video Analytics H2O Driverless AI IBM Spectrum® Scale IBM Spectrum Discover This publication examines the challenges through five different use case examples: Artificial vision Natural language processing (NLP) Planning for the future Machine learning (ML) AI teaming and collaboration This publication targets readers from LOBs, data science teams, and IT departments, and anyone that is interested in understanding how to build an IA to support enterprise AI development and deployment.
Cloud Data Sharing With Ibm Spectrum Scale
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Author : Nikhil Khandelwal
language : en
Publisher: IBM Redbooks
Release Date : 2017-02-14
Cloud Data Sharing With Ibm Spectrum Scale written by Nikhil Khandelwal and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-14 with Computers categories.
This IBM® RedpaperTM publication provides information to help you with the sizing, configuration, and monitoring of hybrid cloud solutions using the Cloud data sharing feature of IBM Spectrum ScaleTM. IBM Spectrum Scale, formerly IBM General Parallel File System (IBM GPFSTM), is a scalable data and file management solution that provides a global namespace for large data sets along with several enterprise features. Cloud data sharing allows for the sharing and use of data between various cloud object storage types and IBM Spectrum Scale. Cloud data sharing can help with the movement of data in both directions, between file systems and cloud object storage, so that data is where it needs to be, when it needs to be there. This paper is intended for IT architects, IT administrators, storage administrators, and those who want to learn more about sizing, configuration, and monitoring of hybrid cloud solutions using IBM Spectrum Scale and Cloud data sharing.
Data Accelerator For Ai And Analytics
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Author : Simon Lorenz
language : en
Publisher: IBM Redbooks
Release Date : 2021-01-20
Data Accelerator For Ai And Analytics written by Simon Lorenz and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-20 with Computers categories.
This IBM® Redpaper publication focuses on data orchestration in enterprise data pipelines. It provides details about data orchestration and how to address typical challenges that customers face when dealing with large and ever-growing amounts of data for data analytics. While the amount of data increases steadily, artificial intelligence (AI) workloads must speed up to deliver insights and business value in a timely manner. This paper provides a solution that addresses these needs: Data Accelerator for AI and Analytics (DAAA). A proof of concept (PoC) is described in detail. This paper focuses on the functions that are provided by the Data Accelerator for AI and Analytics solution, which simplifies the daily work of data scientists and system administrators. This solution helps increase the efficiency of storage systems and data processing to obtain results faster while eliminating unnecessary data copies and associated data management.
Ibm Watson Content Analytics Discovering Actionable Insight From Your Content
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Author : Wei-Dong (Jackie) Zhu
language : en
Publisher: IBM Redbooks
Release Date : 2014-07-07
Ibm Watson Content Analytics Discovering Actionable Insight From Your Content written by Wei-Dong (Jackie) Zhu and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-07 with Computers categories.
IBM® WatsonTM Content Analytics (Content Analytics) Version 3.0 (formerly known as IBM Content Analytics with Enterprise Search (ICAwES)) helps you to unlock the value of unstructured content to gain new actionable business insight and provides the enterprise search capability all in one product. Content Analytics comes with a set of tools and a robust user interface to empower you to better identify new revenue opportunities, improve customer satisfaction, detect problems early, and improve products, services, and offerings. To help you gain the most benefits from your unstructured content, this IBM Redbooks® publication provides in-depth information about the features and capabilities of Content Analytics, how the content analytics works, and how to perform effective and efficient content analytics on your content to discover actionable business insights. This book covers key concepts in content analytics, such as facets, frequency, deviation, correlation, trend, and sentimental analysis. It describes the content analytics miner, and guides you on performing content analytics using views, dictionary lookup, and customization. The book also covers using IBM Content Analytics Studio for domain-specific content analytics, integrating with IBM Content Classification to get categories and new metadata, and interfacing with IBM Cognos® Business Intelligence (BI) to add values in BI reporting and analysis, and customizing the content analytics miner with APIs. In addition, the book describes how to use the enterprise search capability for the discovery and retrieval of documents using various query and visual navigation techniques, and customization of crawling, parsing, indexing, and runtime search to improve search results. The target audience of this book is decision makers, business users, and IT architects and specialists who want to understand and analyze their enterprise content to improve and enhance their business operations. It is also intended as a technical how-to guide for use with the online IBM Knowledge Center for configuring and performing content analytics and enterprise search with Content Analytics.
Digital Management Practice
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Author : Adrian Vogler
language : en
Publisher: Springer Nature
Release Date : 2024-01-28
Digital Management Practice written by Adrian Vogler and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-28 with Business & Economics categories.
The book illustrates how managers and knowledge workers can effectively harness collective and artificial intelligence to counteract the effects of exponential change and successfully implement digitization within their organizations. The author applies the proven management principles of Peter F. Drucker to the new challenges of the digital age, enhancing them with the concepts of collective and artificial intelligence. This approach also takes into account the insights of Daniel Kahneman regarding "Thinking, Fast and Slow" and the associated cognitive biases and deficits in human thinking. By leveraging innovative tools – collective and artificial intelligence – these deficits can be mitigated, aiding in decision-making. The use of these tools in innovation management and work organization is also discussed. Readers are provided with practical tips and strategies for implementation. Embark on an exciting journey through digital management practices and successfully navigate the challenges of the digital world.