Executing Data Quality Projects

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  • Author : Danette McGilvray
  • Publisher : Elsevier
  • Pages : 352 pages
  • ISBN : 0080558399
  • Rating : 5/5 from 1 reviews
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Download or Read online Executing Data Quality Projects full in PDF, ePub and kindle. this book written by Danette McGilvray and published by Elsevier which was released on 01 September 2008 with total page 352 pages. We cannot guarantee that Executing Data Quality Projects book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. Information is currency. Recent studies show that data quality problems are costing businesses billions of dollars each year, with poor data linked to waste and inefficiency, damaged credibility among customers and suppliers, and an organizational inability to make sound decisions. In this important and timely new book, Danette McGilvray presents her “Ten Steps approach to information quality, a proven method for both understanding and creating information quality in the enterprise. Her trademarked approach—in which she has trained Fortune 500 clients and hundreds of workshop attendees—applies to all types of data and to all types of organizations. * Includes numerous templates, detailed examples, and practical advice for executing every step of the “Ten Steps approach. * Allows for quick reference with an easy-to-use format highlighting key concepts and definitions, important checkpoints, communication activities, and best practices. * A companion Web site includes links to numerous data quality resources, including many of the planning and information-gathering templates featured in the text, quick summaries of key ideas from the Ten Step methodology, and other tools and information available online.

Executing Data Quality Projects

Executing Data Quality Projects
  • Author : Danette McGilvray
  • Publisher : Elsevier
  • Release : 01 September 2008
GET THIS BOOK Executing Data Quality Projects

Information is currency. Recent studies show that data quality problems are costing businesses billions of dollars each year, with poor data linked to waste and inefficiency, damaged credibility among customers and suppliers, and an organizational inability to make sound decisions. In this important and timely new book, Danette McGilvray presents her “Ten Steps approach to information quality, a proven method for both understanding and creating information quality in the enterprise. Her trademarked approach—in which she has trained Fortune 500 clients

Executing Data Quality Projects

Executing Data Quality Projects
  • Author : Danette McGilvray
  • Publisher : Academic Press
  • Release : 27 May 2021
GET THIS BOOK Executing Data Quality Projects

Executing Data Quality Projects, Second Edition presents a structured yet flexible approach for creating, improving, sustaining and managing the quality of data and information within any organization. Studies show that data quality problems are costing businesses billions of dollars each year, with poor data linked to waste and inefficiency, damaged credibility among customers and suppliers, and an organizational inability to make sound decisions. Help is here! This book describes a proven Ten Step approach that combines a conceptual framework for

Handbook of Data Quality

Handbook of Data Quality
  • Author : Shazia Sadiq
  • Publisher : Springer Science & Business Media
  • Release : 13 August 2013
GET THIS BOOK Handbook of Data Quality

The issue of data quality is as old as data itself. However, the proliferation of diverse, large-scale and often publically available data on the Web has increased the risk of poor data quality and misleading data interpretations. On the other hand, data is now exposed at a much more strategic level e.g. through business intelligence systems, increasing manifold the stakes involved for individuals, corporations as well as government agencies. There, the lack of knowledge about data accuracy, currency or

Measuring Data Quality for Ongoing Improvement

Measuring Data Quality for Ongoing Improvement
  • Author : Laura Sebastian-Coleman
  • Publisher : Newnes
  • Release : 31 December 2012
GET THIS BOOK Measuring Data Quality for Ongoing Improvement

The Data Quality Assessment Framework shows you how to measure and monitor data quality, ensuring quality over time. You’ll start with general concepts of measurement and work your way through a detailed framework of more than three dozen measurement types related to five objective dimensions of quality: completeness, timeliness, consistency, validity, and integrity. Ongoing measurement, rather than one time activities will help your organization reach a new level of data quality. This plain-language approach to measuring data can be

Competing with High Quality Data

Competing with High Quality Data
  • Author : Rajesh Jugulum
  • Publisher : John Wiley & Sons
  • Release : 10 March 2014
GET THIS BOOK Competing with High Quality Data

Create a competitive advantage with data quality Data is rapidly becoming the powerhouse of industry, butlow-quality data can actually put a company at a disadvantage. Tobe used effectively, data must accurately reflect the real-worldscenario it represents, and it must be in a form that is usable andaccessible. Quality data involves asking the right questions,targeting the correct parameters, and having an effective internalmanagement, organization, and access system. It must be relevant,complete, and correct, while falling in line with pervasiveregulatory

Making Enterprise Information Management EIM Work for Business

Making Enterprise Information Management  EIM  Work for Business
  • Author : John Ladley
  • Publisher : Morgan Kaufmann
  • Release : 03 July 2010
GET THIS BOOK Making Enterprise Information Management EIM Work for Business

Making Enterprise Information Management (EIM) Work for Business: A Guide to Understanding Information as an Asset provides a comprehensive discussion of EIM. It endeavors to explain information asset management and place it into a pragmatic, focused, and relevant light. The book is organized into two parts. Part 1 provides the material required to sell, understand, and validate the EIM program. It explains concepts such as treating Information, Data, and Content as true assets; information management maturity; and how EIM affects organizations.

Integration of Data Mining in Business Intelligence Systems

Integration of Data Mining in Business Intelligence Systems
  • Author : Azevedo, Ana
  • Publisher : IGI Global
  • Release : 30 September 2014
GET THIS BOOK Integration of Data Mining in Business Intelligence Systems

Uncovering and analyzing data associated with the current business environment is essential in maintaining a competitive edge. As such, making informed decisions based on this data is crucial to managers across industries. Integration of Data Mining in Business Intelligence Systems investigates the incorporation of data mining into business technologies used in the decision making process. Emphasizing cutting-edge research and relevant concepts in data discovery and analysis, this book is a comprehensive reference source for policymakers, academicians, researchers, students, technology developers,

Recent Trends in Data Science and Soft Computing

Recent Trends in Data Science and Soft Computing
  • Author : Faisal Saeed,Nadhmi Gazem,Fathey Mohammed,Abdelsalam Busalim
  • Publisher : Springer
  • Release : 08 September 2018
GET THIS BOOK Recent Trends in Data Science and Soft Computing

This book presents the proceedings of the 3rd International Conference of Reliable Information and Communication Technology 2018 (IRICT 2018), which was held in Kuala Lumpur, Malaysia, on July 23–24, 2018. The main theme of the conference was “Data Science, AI and IoT Trends for the Fourth Industrial Revolution.” A total of 158 papers were submitted to the conference, of which 103 were accepted and considered for publication in this book. Several hot research topics are covered, including Advances in Data Science and Big Data Analytics, Artificial

Information Quality and Governance for Business Intelligence

Information Quality and Governance for Business Intelligence
  • Author : Yeoh, William
  • Publisher : IGI Global
  • Release : 31 December 2013
GET THIS BOOK Information Quality and Governance for Business Intelligence

Business intelligence initiatives have been dominating the technology priority list of many organizations. However, the lack of effective information quality and governance strategies and policies has been meeting these initiatives with some challenges. Information Quality and Governance for Business Intelligence presents the latest exchange of academic research on all aspects of practicing and managing information using a multidisciplinary approach that examines its quality for organizational growth. This book is an essential reference tool for researchers, practitioners, and university students specializing

Data Quality

Data Quality
  • Author : Rupa Mahanti
  • Publisher : Quality Press
  • Release : 18 March 2019
GET THIS BOOK Data Quality

“This is not the kind of book that you’ll read one time and be done with. So scan it quickly the first time through to get an idea of its breadth. Then dig in on one topic of special importance to your work. Finally, use it as a reference to guide your next steps, learn details, and broaden your perspective.” from the foreword by Thomas C. Redman, Ph.D., “the Data Doc” Good data is a source of myriad

Entity Resolution and Information Quality

Entity Resolution and Information Quality
  • Author : John R. Talburt
  • Publisher : Elsevier
  • Release : 14 January 2011
GET THIS BOOK Entity Resolution and Information Quality

Entity Resolution and Information Quality presents topics and definitions, and clarifies confusing terminologies regarding entity resolution and information quality. It takes a very wide view of IQ, including its six-domain framework and the skills formed by the International Association for Information and Data Quality {IAIDQ). The book includes chapters that cover the principles of entity resolution and the principles of Information Quality, in addition to their concepts and terminology. It also discusses the Fellegi-Sunter theory of record linkage, the Stanford

Integration Challenges for Analytics Business Intelligence and Data Mining

Integration Challenges for Analytics  Business Intelligence  and Data Mining
  • Author : Azevedo, Ana,Santos, Manuel Filipe
  • Publisher : IGI Global
  • Release : 11 December 2020
GET THIS BOOK Integration Challenges for Analytics Business Intelligence and Data Mining

As technology continues to advance, it is critical for businesses to implement systems that can support the transformation of data into information that is crucial for the success of the company. Without the integration of data (both structured and unstructured) mining in business intelligence systems, invaluable knowledge is lost. However, there are currently many different models and approaches that must be explored to determine the best method of integration. Integration Challenges for Analytics, Business Intelligence, and Data Mining is a

The Philosophy of Information Quality

The Philosophy of Information Quality
  • Author : Luciano Floridi,Phyllis Illari
  • Publisher : Springer
  • Release : 01 August 2014
GET THIS BOOK The Philosophy of Information Quality

This work fulfills the need for a conceptual and technical framework to improve understanding of Information Quality (IQ) and Information Quality standards. The meaning and practical implementation of IQ are addressed, as it is relevant to any field where there is a need to handle data and issues such as accessibility, accuracy, completeness, currency, integrity, reliability, timeliness, usability, the role of metrics and so forth are all a part of Information Quality. In order to support the cross-fertilization of theory

Data Quality

Data Quality
  • Author : Jack E. Olson
  • Publisher : Elsevier
  • Release : 09 January 2003
GET THIS BOOK Data Quality

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.