Cataloging Unstructured Data In Ibm Watson Knowledge Catalog With Ibm Spectrum Discover

Author : Joseph Dain,Abeer Selim,Anil Patil,Christopher Vollmar,Flavio de Rezende,Frank Greco,Frank N. Lee,Isom Crawford Jr.,Ivaylo B. Bozhinov,Joanna Wong,Joshua Blumert,Larry Coyne,IBM Redbooks
Publisher : IBM Redbooks
Page : 108 pages
File Size : 48,8 Mb
Release : 2020-08-11
Category : Computers
ISBN : 9780738459028

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Cataloging Unstructured Data in IBM Watson Knowledge Catalog with IBM Spectrum Discover by Joseph Dain,Abeer Selim,Anil Patil,Christopher Vollmar,Flavio de Rezende,Frank Greco,Frank N. Lee,Isom Crawford Jr.,Ivaylo B. Bozhinov,Joanna Wong,Joshua Blumert,Larry Coyne,IBM Redbooks Pdf

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.

Author : Joseph Dain,Abeer Selim,Anil Patil,Christopher Vollmar,Flavio de Rezende,Frank Greco,Frank Lee,Isom Crawford,Ivaylo Bozhinov,Joanna Wong,Joshua Blumert,Larry Coyne
Publisher : Unknown
Page : 128 pages
File Size : 54,7 Mb
Release : 2020
Category : Database management
ISBN : OCLC:1202816622

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Cataloging Unstructured Data in IBM Watson Knowledge Catalog with IBM Spectrum Discover by Joseph Dain,Abeer Selim,Anil Patil,Christopher Vollmar,Flavio de Rezende,Frank Greco,Frank Lee,Isom Crawford,Ivaylo Bozhinov,Joanna Wong,Joshua Blumert,Larry Coyne Pdf

Author : Joseph Dain,Norman Bogard,Isom Crawford Jr.,Mathias Defiebre,Larry Coyne,IBM Redbooks
Publisher : IBM Redbooks
Page : 152 pages
File Size : 46,9 Mb
Release : 2019-10-01
Category : Computers
ISBN : 9780738457864

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IBM Spectrum Discover: Metadata Management for Deep Insight of Unstructured Storage by Joseph Dain,Norman Bogard,Isom Crawford Jr.,Mathias Defiebre,Larry Coyne,IBM Redbooks Pdf

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.

Author : Ivaylo B. Bozhinov,Isom Crawford Jr.,Joseph Dain,Mathias Defiebre,Maxime Deloche,Kiran Ghag,Vasfi Gucer,Xin Liu,Abeer Selim,Gauthier Siri,Christopher Vollmar,IBM Redbooks
Publisher : IBM Redbooks
Page : 170 pages
File Size : 42,6 Mb
Release : 2020-10-19
Category : Computers
ISBN : 9780738459134

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Making Data Smarter with IBM Spectrum Discover: Practical AI Solutions by Ivaylo B. Bozhinov,Isom Crawford Jr.,Joseph Dain,Mathias Defiebre,Maxime Deloche,Kiran Ghag,Vasfi Gucer,Xin Liu,Abeer Selim,Gauthier Siri,Christopher Vollmar,IBM Redbooks Pdf

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.

Author : Joe Dain
Publisher : Unknown
Page : 128 pages
File Size : 50,7 Mb
Release : 2019
Category : Database management
ISBN : OCLC:1127651150

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IBM Spectrum Discover by Joe Dain Pdf

Author : Scott Vetter,Glen Corneau,Andrew Laidlaw,Marcos Quezada,IBM Redbooks
Publisher : IBM Redbooks
Page : 64 pages
File Size : 52,5 Mb
Release : 2019-09-25
Category : Computers
ISBN : 9780738458052

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IBM Power Systems Enterprise AI Solutions by Scott Vetter,Glen Corneau,Andrew Laidlaw,Marcos Quezada,IBM Redbooks Pdf

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.

Author : Nikhil Khandelwal,Rob Basham,Amey Gokhale,Arend Dittmer,Alexander Safonov,Ryan Marchese,Rishika Kedia,Stan Li,Ranjith Rajagopalan Nair,Larry Coyne,IBM Redbooks
Publisher : IBM Redbooks
Page : 36 pages
File Size : 52,6 Mb
Release : 2017-02-14
Category : Computers
ISBN : 9780738456003

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Cloud Data Sharing with IBM Spectrum Scale by Nikhil Khandelwal,Rob Basham,Amey Gokhale,Arend Dittmer,Alexander Safonov,Ryan Marchese,Rishika Kedia,Stan Li,Ranjith Rajagopalan Nair,Larry Coyne,IBM Redbooks Pdf

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.

Author : Wei-Dong (Jackie) Zhu,Bob Foyle,Daniel Gagné,Vijay Gupta,Josemina Magdalen,Amarjeet S Mundi,Tetsuya Nasukawa,Mark Paulis,Jane Singer,Martin Triska,IBM Redbooks
Publisher : IBM Redbooks
Page : 598 pages
File Size : 51,6 Mb
Release : 2014-07-07
Category : Computers
ISBN : 9780738439426

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IBM Watson Content Analytics: Discovering Actionable Insight from Your Content by Wei-Dong (Jackie) Zhu,Bob Foyle,Daniel Gagné,Vijay Gupta,Josemina Magdalen,Amarjeet S Mundi,Tetsuya Nasukawa,Mark Paulis,Jane Singer,Martin Triska,IBM Redbooks Pdf

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.

Author : Adrian Vogler
Publisher : Springer Nature
Page : 208 pages
File Size : 53,8 Mb
Release : 2024-01-28
Category : Business & Economics
ISBN : 9783662683538

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Digital Management Practice by Adrian Vogler Pdf

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.

Author : Nilesh Suryawanshi,Hemant Kantak,Tan-Long Siau,IBM Redbooks
Publisher : IBM Redbooks
Page : 34 pages
File Size : 54,6 Mb
Release : 2022-09-15
Category : Computers
ISBN : 9780738460819

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SingleStore Database on High Performance IBM Spectrum Scale Filesystem with Red Hat OpenShift and IBM Cloud Pak for Data by Nilesh Suryawanshi,Hemant Kantak,Tan-Long Siau,IBM Redbooks Pdf

This IBM® blueprint describes the SingleStoreDB that is running on Red Hat OpenShift in a containerized environment. The SingleStoreDB deployment uses the IBM Spectrum® Scale container native access storage class to create persistent volumes (PVs) for the SingleStoreDB pods deployment. This document also describes the process that is used to expand a SingleStoreDB volume on IBM Spectrum Scale and an IBM Spectrum Scale PV on a Red Hat OpenShift cluster for IBM Spectrum Scale to verify that the SingleStoreDB remained intact after the volume is expanded. The procedure to create a sample database that is named stockDB, and the data analytical stats for reading and writing the data also are included. The sample data was captured for comparison statistics for SingleStoreDB that is deployed on the IBM Spectrum Scale Cluster File System and local storage. These comparison statistics emphasize the notable difference between the sample data sets. Finally, this document also explains the procedure that is used to create the same sample database with the unlimited storage feature in SingleStore by using IBM Cloud® Object Storage.

Author : Bob Foyle,Daniel Gagné,Vijay Gupta,Josemina Magdalen,Amarjeet Mundi,Tetsuya Nasukawa,Mark Paulis,Jane Singer,Martin Triska,Wei-Dong Zhu
Publisher : Unknown
Page : 598 pages
File Size : 44,8 Mb
Release : 2014
Category : Data mining
ISBN : OCLC:1105804692

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IBM Watson Content Analytics by Bob Foyle,Daniel Gagné,Vijay Gupta,Josemina Magdalen,Amarjeet Mundi,Tetsuya Nasukawa,Mark Paulis,Jane Singer,Martin Triska,Wei-Dong Zhu Pdf

IBM® Watson 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.

Author : Rob Thomas,Paul Zikopoulos
Publisher : "O'Reilly Media, Inc."
Page : 238 pages
File Size : 50,5 Mb
Release : 2020-04-30
Category : Computers
ISBN : 9781492073383

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The AI Ladder by Rob Thomas,Paul Zikopoulos Pdf

AI may be the greatest opportunity of our time, with the potential to add nearly $16 trillion to the global economy over the next decade. But so far, adoption has been much slower than anticipated, or so headlines may lead you to believe. With this practical guide, business leaders will discover where they are in their AI journey and learn the steps necessary to successfully scale AI throughout their organization. Authors Rob Thomas and Paul Zikopoulos from IBM introduce C-suite executives and business professionals to the AI Ladder—a unified, prescriptive approach to help them understand and accelerate the AI journey. Complete with real-world examples and real-life experiences, this book explores AI drivers, value, and opportunity, as well as the adoption challenges organizations face. Understand why you can’t have AI without an information architecture (IA) Appreciate how AI is as much a cultural change as it is a technological one Collect data and make it simple and accessible, regardless of where it lives Organize data to create a business-ready analytics foundation Analyze data, and build and scale AI with trust and transparency Infuse AI throughout your entire business and create intelligent workflows

Author : Whei-Jen Chen,Serena S Chan,Jean-Marc Costecalde,Yolanda H Yates,Harry Yessayan,IBM Redbooks
Publisher : IBM Redbooks
Page : 440 pages
File Size : 55,5 Mb
Release : 2015-05-29
Category : Computers
ISBN : 9780738440712

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Using IBM Enterprise Records by Whei-Jen Chen,Serena S Chan,Jean-Marc Costecalde,Yolanda H Yates,Harry Yessayan,IBM Redbooks Pdf

Records management helps users address evolving governance mandates to meet regulatory, legal, and fiduciary requirements. Proactive adherence to information retention policies and procedures is a critical facet of any compliance strategy. IBM® Enterprise Records helps organizations enforce centralized policy management for file plans, retention schedules, legal preservation holds, and auditing. IBM Enterprise Records enables your organization to securely capture, declare, classify, store, and dispose of electronic and physical records. In this IBM Redbooks® publication, we introduce the records management concept and provide an overview of IBM Enterprise Records. We address records management topics, including the retention schedule, file plan, records ingestion and declaration, records disposition, records hold, and Enterprise Records application programming interfaces (APIs). We also use a case study to describe step-by-step instructions to implement a sample records management solution using Enterprise Records. We provide concrete examples of how to perform tasks, such as file plan creation, records ingestion and declaration, records disposition, and records hold. This book helps you to understand the records management concept, the IBM Enterprise Records features and capabilities, and its use.

Author : Shahir Daya,Nguyen Van Duy,Kameswara Eati,Carlos M Ferreira,Dejan Glozic,Vasfi Gucer,Manav Gupta,Sunil Joshi,Valerie Lampkin,Marcelo Martins,Shishir Narain,Ramratan Vennam,IBM Redbooks
Publisher : IBM Redbooks
Page : 176 pages
File Size : 42,8 Mb
Release : 2016-04-04
Category : Computers
ISBN : 9780738440811

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Microservices from Theory to Practice: Creating Applications in IBM Bluemix Using the Microservices Approach by Shahir Daya,Nguyen Van Duy,Kameswara Eati,Carlos M Ferreira,Dejan Glozic,Vasfi Gucer,Manav Gupta,Sunil Joshi,Valerie Lampkin,Marcelo Martins,Shishir Narain,Ramratan Vennam,IBM Redbooks Pdf

Microservices is an architectural style in which large, complex software applications are composed of one or more smaller services. Each of these microservices focuses on completing one task that represents a small business capability. These microservices can be developed in any programming language. They communicate with each other using language-neutral protocols, such as Representational State Transfer (REST), or messaging applications, such as IBM® MQ Light. This IBM Redbooks® publication gives a broad understanding of this increasingly popular architectural style, and provides some real-life examples of how you can develop applications using the microservices approach with IBM BluemixTM. The source code for all of these sample scenarios can be found on GitHub (https://github.com/). The book also presents some case studies from IBM products. We explain the architectural decisions made, our experiences, and lessons learned when redesigning these products using the microservices approach. Information technology (IT) professionals interested in learning about microservices and how to develop or redesign an application in Bluemix using microservices can benefit from this book.

Author : Steven Astorino,Mark Simmonds
Publisher : MC Press
Page : 0 pages
File Size : 42,5 Mb
Release : 2019-10
Category : Computers
ISBN : 1583478922

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Artificial Intelligence by Steven Astorino,Mark Simmonds Pdf

From humble evolutions in research papers and labs, artificial intelligence (AI)--which encompasses Machine Learning (ML) and Deep Learning (DL)--has matured in its many forms, infused in applications that can learn on their own and become progressively smarter with each interaction and transaction. Coupled with immense stores of data, maturity in CPU and GPU hardware, the invention of new, open source deep learning algorithms, and cloud technologies, operational AI has become available to the masses, setting the wheels in motion for a worldwide AI revolution that has never been seen before. This book attempts to help the reader on their AI journey by covering the concepts of AI, Machine Learning, and Deep Learning in its many forms; key ML and DL algorithms data scientists should learn; ethical challenges for the use of AI; how AI is being used across industries; possible future outlook for AI, and an AI Ladder to help accelerate the AI journey.