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Data Quality
Corporate Information Factory, 2nd Edition
The father of the data warehouse incorporates the latest technologies into his blueprint for integrated decision support systems Having invented the corporate information factory (CIF) to help IT and database managers cut through the jungle of information technologies out there, bestselling author Bill Inmon again teams up with experts Claudia Imhoff and Ryan Sousa to show you how to integrate all key components of the modern information system architecture in a way that meets your evolving business needs.
The Data Warehouse Challenge: Taming Data Chaos
Now, readers have to pull all data together in a single format that is compatible across the many different databases and software platforms used throughout the company. How? This resource shows them how.
Data Quality for the Information Age
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Improving Data Warehouse and Business Information Quality: Methods for Reducing Costs and Increasing Profits
Comprehensive guide to measuring and improving information quality both data warehouses, operational databases and source business processes. Provides checklists for quality data definition and information architecture. Describes how to implement an effective information quality environment with data defect prevention. Author provides a money back warranty (page xxvi). Also available in Japanese.
Metadata Management for Information Control and Business Success
Defining a new approach to data management at the enterprise level, this book takes you beyond information management to information control, where the methods of data capture and manipulation supersede data quantity.
Enterprise Knowledge Management: The Data Quality Approach
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.
Data Resource Quality: Turning Bad Habits into Good Practices
Drawing on over four decades experience in data processing, Brackett examines issues around managing data and architecture for information technology managers. He describes the impact of poor data practices and demonstrates more effective approaches, including the need for formal data names and comprehensive definitions, proper data structures, precise integrity rules, and robust documentation. He includes a glossary of specialized meanings for common English terms.
Improving the Quality of Customer Data (PDF download)
As the Internet becomes an important channel for all businesses, companies are challenged to aggregate a vast array of online data points into their already complex labyrinth of multichannel data repositories.
Data Quality: The Field Guide
Data Quality: The Field Guide provides the practical guidance needed to start and advance a data quality program. It motivates interest in data quality, describes the most important data quality problems facing the typical organization, and outlines what an organization must do to improve. It consists of 36 short chapters in an easy-to-use field guide format. Each chapter describes a single issue and how to address it.
Data Quality: The Accuracy Dimension
Data Quality: The Accuracy Dimension is about assessing the quality of corporate data and improving its accuracy using the data profiling method. Corporate data is increasingly important as companies continue to find new ways to use it. Likewise, improving the accuracy of data in information systems is fast becoming a major goal as companies realize how much it affects their bottom line. Data profiling is a new technology that supports and enhances the accuracy of databases throughout major IT shops. Jack Olson explains data profiling and shows how it fits into the larger picture of data quality.
Math, Myth & Magic - Introduction to Name Search and Matching
This informative and educational look at Name Search & Matching will give you a better understanding of the problem and how to begin solving it. With name, address, and identification data; variation, error and fraud are inevitable. This FREE book will help you overcome these problems.
Spatial Data Quality
As research in the geosciences and social sciences becomes increasingly dependent on computers, applications such as geographical information systems are becoming indispensable tools. But the digital representations of phenomena that these systems require are often of poor quality, leading to inaccurate results, uncertainty, error propagation, and potentially legal liability. Spatial data quality has become an essential research topic within geographical information science.
Business Intelligence: The Savvy Manager's Guide
Business Intelligence describes the basic architectural components of a business intelligence environment, ranging from traditional topics such as business process modeling, data modeling, and more modern topics such as business rule systems, data profiling, information compliance and data quality, data warehousing, and data mining. This book progresses through a logical sequence, starting with data model infrastructure, then data preparation, followed by data analysis, integration, knowledge discovery, and finally the actual use of discovered knowledge. The book contains a quick reference guide for business intelligence terminology. Business Intelligence is part of Morgan Kaufmann's Savvy Manager's Guide series.
Exploratory Data Mining and Data Cleaning
- Written for practitioners of data mining, data cleaning and database management.
- Presents a technical treatment of data quality including process, metrics, tools and algorithms.
- Focuses on developing an evolving modeling strategy through an iterative data exploration loop and incorporation of domain knowledge.
- Addresses methods of detecting, quantifying and correcting data quality issues that can have a significant impact on findings and decisions, using commercially available tools as well as new algorithmic approaches.
- Uses case studies to illustrate applications in real life scenarios.
- Highlights new approaches and methodologies, such as the DataSphere space partitioning and summary based analysis techniques.
Security Planning and Disaster Recovery
Proactively implement a successful security and disaster recovery plan--before a security breach occurs. Including hands- on security checklists, design maps, and sample plans, this expert resource is crucial for keeping your network safe from any outside intrusions.
Sharpening Your SAS Skills
Sharpening Your SAS Skills is an intermediate text on SAS programming and data management intended for those with some knowledge of the SAS language. It covers the most common tools used by SAS programmers and data analysts in their daily work. Designed as a quick-reference and practitioner's guide, this book will be particularly useful for those preparing for the SAS Base Programming exam. The book includes question and answers at the end of each section to reinforce the reader's knowledge of the topic and tables in each chapter that summarize the syntax and expected data. A companion Web site contains examples, extra exercises, the list and log SAS files, and the pdf/html output files.
Six Sigma for IT Management
This is a unique publication, giving the application of the Six Sigma approach in combination with ITIL best practice. Six Sigma provides a quantitative methodology of continuous (process) improvement and cost reduction, by reducing the amount of variation in process outcomes. This book demonstrates how IT can be made to work as an enabler to better business processes.
Journey to Data Quality
All organizations today confront data quality problems, both systemic and structural. Neither ad hoc approaches nor fixes at the systems level - installing the latest software or developing an expensive data warehouse - solve the basic problem of bad data quality practices. This book offers a roadmap that can be used by practitioners, executives and students for planning and implementing a viable data and information quality management program. This practical guide, based on rigorous research and informed by real-world examples, describes the challenges of data management and provides the principles, strategies, tools and techniques necessary to meet them.
Introduction to Data Mining Using SAS Enterprise Miner
If you have an abundance of data, but no idea what to do with it, this book was written for you! Packed with examples from an array of industries, this introductory text provides you with excellent starting points and practical guidelines to begin data mining today. The author encourages you to think of data mining as a process of exploration rather than as a collection of tools to investigate data. In that way, you choose the methods that will extract the most information from your data, and, while there are no right answers to investigating data sets, there are many questions that can be asked to produce meaningful results. Each answer then creates a path that helps you drill down to explore the data fully. It is up to you to determine what is of interest and what is important to analyze.
The Complete Idiot's Guide to Lean Six Sigma
The perfect mix for a productive company ...
Increasingly popular with large and mid-sized companies around the world, Lean Six Sigma is the new hybridization of Six Sigma and Lean methodologies. Packed with diagrams and real-life examples, this book reveals the four keys of Lean Six Sigma and how to apply them to one's job. Also included are the concepts, tools, templates, tips, examples, and implementation steps required to move through its process
Data Quality Assessment
Editorial Review
This is one of those books that marks a milestone in the evolution of a discipline. Arkady's insights and techniques fuel the transition of data quality management from art to science -- from crafting to engineering. From deep experience, with thoughtful structure, and with engaging style Arkady brings the discipline of data quality to practitioners. -- David Wells, Director of Education, Data Warehousing Institute.
Data Mining VIII: Data, Text and Web Mining and their Business Applications
Bringing together papers presented at the Eighth International Conference on Data, Text and Web Mining and their Business Applications, this book addresses the new developments in the important field of information engineering. The book, edited by A. Zanasi, (TEMIS Text Mining Solutions, Italy, Italy), C. A. Brebbia (Wessex Institute of Technology, Southampton, UK) and N. F. F. Ebecken (COPPE/Federal University of Rio de Janeiro, Brazil) features contributions on categorization methods; data preparation; enterprise information systems; mining environmental and geospatial data; text mining; applications in business, industry and customer relationship management; and national security.
Full contents details on the book can be found at www.witpressusa.com.
Data Quality Assessment
Review
DATA QUALITY ASSESSMENT is an excellent book and a must read for any data quality professional. Arkady packs years of experience in data quality into comprehensive step-by-step instructions for practitioners of all levels.
--R. Michael Levin, Sr. Database Architect, Lockheed Martin
