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Original Essays | September 18, 2014

Lin Enger: IMG Knowing vs. Knowing



On a hot July evening years ago, my Toyota Tercel overheated on a flat stretch of highway north of Cedar Rapids, Iowa. A steam geyser shot up from... Continue »
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Enterprise Knowledge Management: The Data Quality Approach

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Synopses & Reviews

Publisher Comments:

Your company captures and stores tremendous amounts of information about every aspect of its business. But with this rise in the quantity of information has come a corresponding decrease in its quality. Now more than ever, reversing this trend may spell the difference between success and failure. How can you and your organization respond to this challenge?

Enterprise Knowledge Management gives you just what you need: a precise yet adaptable methodology for defining, measuring, and improving data quality and managing business intelligence. This one-of-a-kind book begins by laying out an economic framework for understanding the real business value of data quality. It then outlines rules for measuring data quality and determining where it can and should be improved. Finally, it teaches proven techniques through which you can achieve meaningful advances in the quality of your business data, including domain- and mapping-based consolidation of enterprise knowledge.

Features

  • Expert advice from a highly successful data quality consultant.

  • Rigorously methodical in its approach to the problem and the detailed solution it presents.

  • Teaches you to measure quality in real business terms and to achieve meaningful, demonstrable improvement.

  • Uniquely combines business acumen and technical expertise-an indispensable resource for managers and IT professionals alike.

  • Documents the high costs of bad data and details the options available to any company that wants to transform mere data into true enterprise knowledge.

Synopsis:

ailable to any company that wants to transform mere data into true enterprise knowledge.

Synopsis:

Today, companies capture and store tremendous amounts of information about every aspect of their business: their customers, partners, vendors, markets, and more. But with the rise in the quantity of information has come a corresponding decrease in its quality--a problem businesses recognize and are working feverishly to solve.

Enterprise Knowledge Management: The Data Quality Approach presents an easily adaptable methodology for defining, measuring, and improving data quality. Author David Loshin begins by presenting an economic framework for understanding the value of data quality, then proceeds to outline data quality rules and domain-and mapping-based approaches to consolidating enterprise knowledge. Written for both a managerial and a technical audience, this book will be indispensable to the growing number of companies committed to wresting every possible advantage from their vast stores of business information.

Key Features

* Expert advice from a highly successful data quality consultant

* The only book on data quality offering the business acumen to appeal to managers and the technical expertise to appeal to IT professionals

* Details the high costs of bad data and the options available to companies that want to transform mere data into true enterprise knowledge

* Presents conceptual and practical information complementing companies' interest in data warehousing, data mining, and knowledge discovery

About the Author

David Loshin, is the president and Chief Technology Officer of Knowledge Integrity, holds a M.S. degree in Computer Science from Cornell University, and is the author of two books: High Performance Computing Demystified, AP Professional, 1994, and Efficient Memory Programming, McGraw-Hill, 1998.

Table of Contents

Preface

Chapter 1 - Introduction

Chapter 2 - Who Owns Information?

Chapter 3 - Data Quality in Practice

Chapter 4 - Economic Framework of Data Quality and the Value Proposition

Chapter 5 - Dimensions of Data Quality

Chapter 6 - Statistical Process Control and the Improvement Cycle

Chapter 7 - Domains, Mappings, and Enterprise Reference Data

Chapter 8 - Data Quality Assertions and Business Rules

Chapter 9 - Measurement and Current State Assessment

Chapter 10 - Data Quality Requirements

Chapter 11 - Metadata, Guidelines, and Policy

Chapter 12 - Rule-Based Data Quality

Chapter 13 - Metadata and Rule Discovery

Chapter 14 - Data Cleansing

Chapter 15 - Root Cause Analysis and Supplier Management

Chapter 16 - Data Enrichment/Enhancement

Chapter 17 - Data Quality and Business Rules in Practice

Chapter 18 - Building the Data Quality Practice

Product Details

ISBN:
9780124558403
Author:
Loshin, David
Publisher:
Morgan Kaufmann Publishers
Location:
San Diego, Calif.
Subject:
Management
Subject:
Quality Control
Subject:
Industrial Management
Subject:
Management Information Systems
Subject:
Business enterprises
Subject:
Database Management - General
Subject:
Data warehousing
Subject:
Knowledge management
Subject:
Information Storage & Retrieval
Subject:
Information technology -- Management.
Subject:
Database applications
Edition Description:
Includes index.
Series:
The Morgan Kaufmann Series in Data Management Systems
Series Volume:
2
Publication Date:
20010131
Binding:
HARDCOVER
Language:
English
Illustrations:
Yes
Pages:
493
Dimensions:
9.25 x 7 in.

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Related Subjects

Business » High Tech Management
Business » Quality and Total Quality Management TQM
Computers and Internet » Database » Applications
Computers and Internet » Database » Design
Computers and Internet » Internet » Information
Computers and Internet » Software Engineering » General
Computers and Internet » Software Engineering » Software Management
Health and Self-Help » Health and Medicine » Medical Specialties
Reference » Science Reference » Technology
Science and Mathematics » Biology » General

Enterprise Knowledge Management: The Data Quality Approach New Hardcover
0 stars - 0 reviews
$96.95 In Stock
Product details 493 pages Morgan Kaufmann Publishers - English 9780124558403 Reviews:
"Synopsis" by , ailable to any company that wants to transform mere data into true enterprise knowledge.
"Synopsis" by , Today, companies capture and store tremendous amounts of information about every aspect of their business: their customers, partners, vendors, markets, and more. But with the rise in the quantity of information has come a corresponding decrease in its quality--a problem businesses recognize and are working feverishly to solve.

Enterprise Knowledge Management: The Data Quality Approach presents an easily adaptable methodology for defining, measuring, and improving data quality. Author David Loshin begins by presenting an economic framework for understanding the value of data quality, then proceeds to outline data quality rules and domain-and mapping-based approaches to consolidating enterprise knowledge. Written for both a managerial and a technical audience, this book will be indispensable to the growing number of companies committed to wresting every possible advantage from their vast stores of business information.

Key Features

* Expert advice from a highly successful data quality consultant

* The only book on data quality offering the business acumen to appeal to managers and the technical expertise to appeal to IT professionals

* Details the high costs of bad data and the options available to companies that want to transform mere data into true enterprise knowledge

* Presents conceptual and practical information complementing companies' interest in data warehousing, data mining, and knowledge discovery

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