Cataloging Unstructured Data In Ibm Watson Knowledge Catalog With Ibm Spectrum Discover
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| Author | : Joseph Dain |
| Publisher | : IBM Redbooks |
| Total Pages | : 108 |
| Release | : 2020-08-11 |
| Genre | : Computers |
| ISBN | : 073845902X |
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 |
| Publisher | : |
| Total Pages | : |
| Release | : 2020 |
| Genre | : Database management |
| ISBN | : |
| Author | : Scott Vetter |
| Publisher | : IBM Redbooks |
| Total Pages | : 64 |
| Release | : 2019-09-25 |
| Genre | : Computers |
| ISBN | : 0738458058 |
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 | : Adrian Vogler |
| Publisher | : Springer Nature |
| Total Pages | : 208 |
| Release | : 2024-01-28 |
| Genre | : Business & Economics |
| ISBN | : 3662683539 |
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 | : Joseph Dain |
| Publisher | : IBM Redbooks |
| Total Pages | : 152 |
| Release | : 2019-10-01 |
| Genre | : Computers |
| ISBN | : 0738457868 |
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 | : Whei-Jen Chen |
| Publisher | : IBM Redbooks |
| Total Pages | : 510 |
| Release | : 2011-01-17 |
| Genre | : Computers |
| ISBN | : 0738434701 |
IBM® Informix® is a low-administration, easy-to-use, and embeddable database that is ideal for application development. It supports a wide range of development platforms, such as JavaTM, .NET, PHP, and web services, enabling developers to build database applications in the language of their choice. Informix is designed to handle RDBMS data and XML without modification and can be extended easily to handle new data sets. This IBM Redbooks® publication provides fundamentals of Informix application development. It covers the Informix Client installation and configuration for application development environments. It discusses the skills and techniques for building Informix applications with Java, ESQL/C, OLE DB, .NET, PHP, Ruby on Rails, DataBlade®, and Hibernate. The book uses code examples to demonstrate how to develop an Informix application with various drivers, APIs, and interfaces. It also provides application development troubleshooting and considerations for performance. This book is intended for developers who use IBM Informix for application development. Although some of the topics that we discuss are highly technical, the information in the book might also be helpful for managers or database administrators who are looking to better understand their Informix development environment.
| Author | : Whei-Jen Chen |
| Publisher | : IBM Redbooks |
| Total Pages | : 440 |
| Release | : 2015-05-29 |
| Genre | : Computers |
| ISBN | : 073844071X |
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 | : Steven Astorino |
| Publisher | : MC Press |
| Total Pages | : 0 |
| Release | : 2019-10 |
| Genre | : Computers |
| ISBN | : 9781583478929 |
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.
| Author | : Malcolm S. Knowles |
| Publisher | : Routledge |
| Total Pages | : 407 |
| Release | : 2020-12-20 |
| Genre | : Business & Economics |
| ISBN | : 1000072894 |
How do you tailor education to the learning needs of adults? Do they learn differently from children? How does their life experience inform their learning processes? These were the questions at the heart of Malcolm Knowles’ pioneering theory of andragogy which transformed education theory in the 1970s. The resulting principles of a self-directed, experiential, problem-centred approach to learning have been hugely influential and are still the basis of the learning practices we use today. Understanding these principles is the cornerstone of increasing motivation and enabling adult learners to achieve. The 9th edition of The Adult Learner has been revised to include: Updates to the book to reflect the very latest advancements in the field. The addition of two new chapters on diversity and inclusion in adult learning, and andragogy and the online adult learner. An updated supporting website. This website for the 9th edition of The Adult Learner will provide basic instructor aids including a PowerPoint presentation for each chapter. Revisions throughout to make it more readable and relevant to your practices. If you are a researcher, practitioner, or student in education, an adult learning practitioner, training manager, or involved in human resource development, this is the definitive book in adult learning you should not be without.
| Author | : Zikopoulos |
| Publisher | : McGraw-Hill/Osborne Media |
| Total Pages | : 392 |
| Release | : 2014-11-10 |
| Genre | : Big data |
| ISBN | : 9780071844659 |
Big Data in a nutshell: It is the ability to retain, process, and understand data like never before. It can mean more data than what you are using today; but it can also mean different kinds of data, a venture into the unstructured world where most of today's data resides. In this book you will learn how cognitive computing systems, like IBM Watson, fit into the Big Data world. Learn about the concept of data-in-motion and InfoSphere Streams, the world's fastest and most flexible platform for streaming data. Capturing, storing, refining, transforming, governing, securing, and analyzing data are important topics also covered in this book.
