Knowledge Management: Learning from Knowledge Engineering

CRC Press
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Knowledge Management (KM) is strongly rooted in the discipline of Knowledge Engineering (KE), which in turn grew partly out of the artificial intelligence field. Despite their close relationship, however, many KM specialists have failed to fully recognize the synergy or acknowledge the power that KE methodologies, techniques, and tools hold for enhancing the state of the art in Knowledge Management.

Knowledge Management: Learning from Knowledge Engineering addresses this vacuum. It gives concise, practical information and insights drawn from the author's many years of experience in the fields of expert systems and Knowledge Management. Based upon research, analyses, and illustrative case studies, this is the first book to integrate the theory and practice of artificial intelligence and expert systems with the current organizational and strategic aspects of Knowledge Management.

The time has come for Knowledge Management professionals to appreciate the synergy between their work and the work of their counterparts in Knowledge Engineering. Knowledge Management: Learning from Knowledge Engineering is the ideal starting point for those in KM to learn from and exploit advances in that field, and thereby advance their own.
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Additional Information

Publisher
CRC Press
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Published on
Mar 28, 2001
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Pages
152
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ISBN
9781420041125
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Language
English
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Genres
Business & Economics / General
Business & Economics / Management Science
Computers / Information Technology
Computers / Networking / General
Technology & Engineering / Engineering (General)
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Content Protection
This content is DRM protected.
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Available on Android devices
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Eligible for Family Library

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"The chapters in this volume offer useful case studies, technical roadmaps, lessons learned, and a few prescriptions to ‘do this, avoid that.’"
—From the Foreword by Joe LaCugna, Ph.D., Enterprise Analytics and Business Intelligence, Starbucks Coffee Company

With the growing barrage of "big data," it becomes vitally important for organizations to make sense of this data and information in a timely and effective way. That’s where analytics come into play. Research shows that organizations that use business analytics to guide their decision making are more productive and experience higher returns on equity. Big Data and Business Analytics helps you quickly grasp the trends and techniques of big data and business analytics to make your organization more competitive.

Packed with case studies, this book assembles insights from some of the leading experts and organizations worldwide. Spanning industry, government, not-for-profit organizations, and academia, they share valuable perspectives on big data domains such as cybersecurity, marketing, emergency management, healthcare, finance, and transportation.

Understand the trends, potential, and challenges associated with big data and business analytics Get an overview of machine learning, advanced statistical techniques, and other predictive analytics that can help you solve big data issues Learn from VPs of Big Data/Insights & Analytics via case studies of Fortune 100 companies, government agencies, universities, and not-for-profits

Big data problems are complex. This book shows you how to go from being data-rich to insight-rich, improving your decision making and creating competitive advantage.

Author Jay Liebowitz recently had an article published in The World Financial Review.

www.worldfinancialreview.com/?p=1904
Now a New York Times and Wall Street Journal bestseller

"I raced through Radical Candor--It’s thrilling to learn a framework that shows how to be both a better boss and a better colleague. Radical Candor is packed with illuminating truths, insightful advice, and practical suggestions, all illustrated with engaging (and often funny) stories from Kim Scott’s own experiences at places like Apple, Google, and various start-ups. Indispensable." —Gretchen Rubin author of New York Times bestseller The Happiness Project

"Reading Radical Candor will help you build, lead, and inspire teams to do the best work of their lives. Kim Scott's insights--based on her experience, keen observational intelligence and analysis--will help you be a better leader and create a more effective organization." —Sheryl Sandberg author of the New York Times bestseller Lean In

"Kim Scott has a well-earned reputation as a kick-ass boss and a voice that CEOs take seriously. In this remarkable book, she draws on her extensive experience to provide clear and honest guidance on the fundamentals of leading others: how to give (and receive) feedback, how to make smart decisions, how to keep moving forward, and much more. If you manage people--whether it be 1 person or a 1,000--you need Radical Candor. Now." —Daniel Pink author of New York Times bestseller Drive

From the time we learn to speak, we’re told that if you don’t have anything nice to say, don’t say anything at all. When you become a manager, it’s your job to say it--and your obligation.

Author Kim Scott was an executive at Google and then at Apple, where she worked with a team to develop a class on how to be a good boss. She has earned growing fame in recent years with her vital new approach to effective management, Radical Candor.

Radical Candor is a simple idea: to be a good boss, you have to Care Personally at the same time that you Challenge Directly. When you challenge without caring it’s obnoxious aggression; when you care without challenging it’s ruinous empathy. When you do neither it’s manipulative insincerity.

This simple framework can help you build better relationships at work, and fulfill your three key responsibilities as a leader: creating a culture of feedback (praise and criticism), building a cohesive team, and achieving results you’re all proud of.

Radical Candor offers a guide to those bewildered or exhausted by management, written for bosses and those who manage bosses. Taken from years of the author’s experience, and distilled clearly giving actionable lessons to the reader; it shows managers how to be successful while retaining their humanity, finding meaning in their job, and creating an environment where people both love their work and their colleagues.

Strategic intelligence (SI) has mostly been used in military settings, but its worth goes well beyond that limited role. It has become invaluable for improving any organization's strategic decision making process. The author of Strategic Intelligence: Business Intelligence, Competitive Intelligence, and Knowledge Management recognizes synergies among component pieces of strategic intelligence, and demonstrates how executives can best use this internal and external information toward making better decisions.

Divided into two major parts, the book first discusses the convergence of knowledge management (KM), business intelligence (BI), and competitive intelligence (CI) into what the author defines as strategic intelligence. The second part of the volume describes case studies written by recognized experts in the fields of KM, BI, and CI. The case studies include strategic scenarios at Motorola, AARP, Northrop Grumman, and other market leaders.

About the Editor
Jay Liebowitz, D.Sc., is a full professor in the Graduate Division of Business and Management and program director for the Graduate Certificate in Competitive Intelligence at Johns Hopkins University.
The first knowledge management officer at NASA Goddard Space Flight Center, he also served as the Robert W. Deutsch Distinguished Professor of Information Systems at the University of Maryland-Baltimore County, professor of Management Science at George Washington University, and Chaired Professor of Artificial Intelligence (AI) at the U.S. Army War College. A founder and chairperson of The World Congress on Expert Systems, he is a Fulbright Scholar, IEEE-USA Federal Communications Commission Executive Fellow, and Computer Educator of the Year (International Association for Computer Information Systems).
As we get caught up in the quagmire of Big Data and analytics, it remains critically important to be able to reflect and apply insights, experience, and intuition to your decision-making process. In fact, a recent research study at Tel Aviv University found that executives who relied on their intuition were 90 percent accurate in their decisions.

Bursting the Big Data Bubble: The Case for Intuition-Based Decision Making focuses on this intuition-based decision making. The book does not discount data-based decision making, especially for decisions that are important and complex. Instead, it emphasizes the importance of applying intuition, gut feel, spirituality, experiential learning, and insight as key factors in the executive decision-making process.

Explaining how intuition is a product of past experience, learning, and ambient factors, the text outlines methods that will help to enhance your data-driven decision-making process with intuition-based decision making. The first part of the book, the "Research Track", presents contributions from leading researchers worldwide on the topic of intuition-based decision making as applied to management.

In the second part of the book, the "Practice Track," global executives and senior managers in industry, government, universities, and not-for-profits present vignettes that illustrate how they have used their intuition in making key decisions.

The research part of the book helps to frame the problem and address leading research in intuition-based decision making. The second part then explains how to apply these intuition-based concepts and issues in your own decision-making process.
As baby boomers approach retirement age and the work patterns of younger workers constantly change, many organizations worldwide are experiencing a far-reaching knowledge bleed. Therefore, it is imperative that organizations find ways to best leverage and retain that vital knowledge before workers leave the organization and attrition occurs.

Answers the Call of Businesses Worldwide

In light of global workforce changes, many organizations’ are faced with a dilemma – how to maintain the right set of people at the right time in order to meet the company’s long-term goals and vision. Knowledge Retention: Strategies and Solutions supplies the answer in the form of strategic human capital management. Written by one of the most sought after knowledge management experts, this easy-to-read, concise guide helps companies adopt proven retention strategies and techniques to capture and share knowledge which is otherwise at risk of being lost in transition. The text also discusses key case studies by leading organizations applying knowledge retention strategies.

Build Institutional Memory and Social Networks

Addresses These Important Questions: How do you know what knowledge is important to capture? What is the best approach to developing a knowledge retention framework? How do you calculate the loss of knowledge? What are the appropriate steps once the damage is assessed? How do you identify knowledge flows and gaps in an organization?

Since you never know when someone will retire or move on, the book emphasizes the importance of minimizing business disruption and accelerating competency development. Operating around four key framework pillars – competency, performance, knowledge, and change management – this text demonstrates why a knowledge-retention strategy should be woven into an organization’s fabric from day one.

Strategic intelligence (SI) has mostly been used in military settings, but its worth goes well beyond that limited role. It has become invaluable for improving any organization's strategic decision making process. The author of Strategic Intelligence: Business Intelligence, Competitive Intelligence, and Knowledge Management recognizes synergies among component pieces of strategic intelligence, and demonstrates how executives can best use this internal and external information toward making better decisions.

Divided into two major parts, the book first discusses the convergence of knowledge management (KM), business intelligence (BI), and competitive intelligence (CI) into what the author defines as strategic intelligence. The second part of the volume describes case studies written by recognized experts in the fields of KM, BI, and CI. The case studies include strategic scenarios at Motorola, AARP, Northrop Grumman, and other market leaders.

About the Editor
Jay Liebowitz, D.Sc., is a full professor in the Graduate Division of Business and Management and program director for the Graduate Certificate in Competitive Intelligence at Johns Hopkins University.
The first knowledge management officer at NASA Goddard Space Flight Center, he also served as the Robert W. Deutsch Distinguished Professor of Information Systems at the University of Maryland-Baltimore County, professor of Management Science at George Washington University, and Chaired Professor of Artificial Intelligence (AI) at the U.S. Army War College. A founder and chairperson of The World Congress on Expert Systems, he is a Fulbright Scholar, IEEE-USA Federal Communications Commission Executive Fellow, and Computer Educator of the Year (International Association for Computer Information Systems).
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