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Entity Information Life Cycle for Big Data

Entity Information Life Cycle for Big Data
  • Author : John R. Talburt
  • Publsiher : Morgan Kaufmann
  • Release : 20 April 2015
  • ISBN : 012800665X
  • Pages : 254 pages
  • Rating : 4/5 from 21 ratings
GET THIS BOOKEntity Information Life Cycle for Big Data

Summary:
Entity Information Life Cycle for Big Data walks you through the ins and outs of managing entity information so you can successfully achieve master data management (MDM) in the era of big data. This book explains big data’s impact on MDM and the critical role of entity information management system (EIMS) in successful MDM. Expert authors Dr. John R. Talburt and Dr. Yinle Zhou provide a thorough background in the principles of managing the entity information life cycle and provide practical tips and techniques for implementing an EIMS, strategies for exploiting distributed processing to handle big data for EIMS, and examples from real applications. Additional material on the theory of EIIM and methods for assessing and evaluating EIMS performance also make this book appropriate for use as a textbook in courses on entity and identity management, data management, customer relationship management (CRM), and related topics. Explains the business value and impact of entity information management system (EIMS) and directly addresses the problem of EIMS design and operation, a critical issue organizations face when implementing MDM systems Offers practical guidance to help you design and build an EIM system that will successfully handle big data Details how to measure and evaluate entity integrity in MDM systems and explains the principles and processes that comprise EIM Provides an understanding of features and functions an EIM system should have that will assist in evaluating commercial EIM systems Includes chapter review questions, exercises, tips, and free downloads of demonstrations that use the OYSTER open source EIM system Executable code (Java .jar files), control scripts, and synthetic input data illustrate various aspects of CSRUD life cycle such as identity capture, identity update, and assertions


Entity Information Life Cycle for Big Data

Entity Information Life Cycle for Big Data
  • Author : John R. Talburt,Yinle Zhou
  • Publisher : Morgan Kaufmann
  • Release : 20 April 2015
GET THIS BOOKEntity Information Life Cycle for Big Data

Entity Information Life Cycle for Big Data walks you through the ins and outs of managing entity information so you can successfully achieve master data management (MDM) in the era of big data. This book explains big data’s impact on MDM and the critical role of entity information management system (EIMS) in successful MDM. Expert authors Dr. John R. Talburt and Dr. Yinle Zhou provide a thorough background in the principles of managing the entity information life cycle and


Handbook of Research on Big Data Storage and Visualization Techniques

Handbook of Research on Big Data Storage and Visualization Techniques
  • Author : Segall, Richard S.,Cook, Jeffrey S.
  • Publisher : IGI Global
  • Release : 05 January 2018
GET THIS BOOKHandbook of Research on Big Data Storage and Visualization Techniques

The digital age has presented an exponential growth in the amount of data available to individuals looking to draw conclusions based on given or collected information across industries. Challenges associated with the analysis, security, sharing, storage, and visualization of large and complex data sets continue to plague data scientists and analysts alike as traditional data processing applications struggle to adequately manage big data. The Handbook of Research on Big Data Storage and Visualization Techniques is a critical scholarly resource that


Information Quality in Information Fusion and Decision Making

Information Quality in Information Fusion and Decision Making
  • Author : Éloi Bossé,Galina L. Rogova
  • Publisher : Springer
  • Release : 02 April 2019
GET THIS BOOKInformation Quality in Information Fusion and Decision Making

This book presents a contemporary view of the role of information quality in information fusion and decision making, and provides a formal foundation and the implementation strategies required for dealing with insufficient information quality in building fusion systems for decision making. Information fusion is the process of gathering, processing, and combining large amounts of information from multiple and diverse sources, including physical sensors to human intelligence reports and social media. That data and information may be unreliable, of low fidelity,



Analytic Methods in Systems and Software Testing

Analytic Methods in Systems and Software Testing
  • Author : Ron S. Kenett,Fabrizio Ruggeri,Frederick W. Faltin
  • Publisher : John Wiley & Sons
  • Release : 04 September 2018
GET THIS BOOKAnalytic Methods in Systems and Software Testing

A comprehensive treatment of systems and software testing using state of the art methods and tools This book provides valuable insights into state of the art software testing methods and explains, with examples, the statistical and analytic methods used in this field. Numerous examples are used to provide understanding in applying these methods to real-world problems. Leading authorities in applied statistics, computer science, and software engineering present state-of-the-art methods addressing challenges faced by practitioners and researchers involved in system and


Entity Resolution and Information Quality

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


New Horizons for a Data-Driven Economy

New Horizons for a Data-Driven Economy
  • Author : José María Cavanillas,Edward Curry,Wolfgang Wahlster
  • Publisher : Springer
  • Release : 04 April 2016
GET THIS BOOKNew Horizons for a Data-Driven Economy

In this book readers will find technological discussions on the existing and emerging technologies across the different stages of the big data value chain. They will learn about legal aspects of big data, the social impact, and about education needs and requirements. And they will discover the business perspective and how big data technology can be exploited to deliver value within different sectors of the economy. The book is structured in four parts: Part I “The Big Data Opportunity” explores


Big Data Integration

Big Data Integration
  • Author : Xin Luna Dong,Divesh Srivastava
  • Publisher : Morgan & Claypool Publishers
  • Release : 01 February 2015
GET THIS BOOKBig Data Integration

The big data era is upon us: data are being generated, analyzed, and used at an unprecedented scale, and data-driven decision making is sweeping through all aspects of society. Since the value of data explodes when it can be linked and fused with other data, addressing the big data integration (BDI) challenge is critical to realizing the promise of big data. BDI differs from traditional data integration along the dimensions of volume, velocity, variety, and veracity. First, not only can


Business Intelligence Guidebook

Business Intelligence Guidebook
  • Author : Rick Sherman
  • Publisher : Newnes
  • Release : 04 November 2014
GET THIS BOOKBusiness Intelligence Guidebook

Between the high-level concepts of business intelligence and the nitty-gritty instructions for using vendors’ tools lies the essential, yet poorly-understood layer of architecture, design and process. Without this knowledge, Big Data is belittled – projects flounder, are late and go over budget. Business Intelligence Guidebook: From Data Integration to Analytics shines a bright light on an often neglected topic, arming you with the knowledge you need to design rock-solid business intelligence and data integration processes. Practicing consultant and adjunct BI professor


Master Data Management

Master Data Management
  • Author : David Loshin
  • Publisher : Morgan Kaufmann
  • Release : 28 July 2010
GET THIS BOOKMaster Data Management

The key to a successful MDM initiative isn’t technology or methods, it’s people: the stakeholders in the organization and their complex ownership of the data that the initiative will affect. Master Data Management equips you with a deeply practical, business-focused way of thinking about MDM—an understanding that will greatly enhance your ability to communicate with stakeholders and win their support. Moreover, it will help you deserve their support: you’ll master all the details involved in planning


Managing Data in Motion

Managing Data in Motion
  • Author : April Reeve
  • Publisher : Newnes
  • Release : 26 February 2013
GET THIS BOOKManaging Data in Motion

Managing Data in Motion describes techniques that have been developed for significantly reducing the complexity of managing system interfaces and enabling scalable architectures. Author April Reeve brings over two decades of experience to present a vendor-neutral approach to moving data between computing environments and systems. Readers will learn the techniques, technologies, and best practices for managing the passage of data between computer systems and integrating disparate data together in an enterprise environment. The average enterprise's computing environment is comprised of


Big Data

Big Data
  • Author : Min Chen,Shiwen Mao,Yin Zhang,Victor C.M. Leung
  • Publisher : Springer
  • Release : 05 May 2014
GET THIS BOOKBig Data

This Springer Brief provides a comprehensive overview of the background and recent developments of big data. The value chain of big data is divided into four phases: data generation, data acquisition, data storage and data analysis. For each phase, the book introduces the general background, discusses technical challenges and reviews the latest advances. Technologies under discussion include cloud computing, Internet of Things, data centers, Hadoop and more. The authors also explore several representative applications of big data such as enterprise


Big Data in Practice

Big Data in Practice
  • Author : Bernard Marr
  • Publisher : John Wiley & Sons
  • Release : 22 March 2016
GET THIS BOOKBig Data in Practice

The best-selling author of Big Data is back, this time with a unique and in-depth insight into how specific companies use big data. Big data is on the tip of everyone's tongue. Everyone understands its power and importance, but many fail to grasp the actionable steps and resources required to utilise it effectively. This book fills the knowledge gap by showing how major companies are using big data every day, from an up-close, on-the-ground perspective. From technology, media and retail,


Data Architecture: A Primer for the Data Scientist

Data Architecture: A Primer for the Data Scientist
  • Author : W.H. Inmon,Daniel Linstedt,Mary Levins
  • Publisher : Academic Press
  • Release : 30 April 2019
GET THIS BOOKData Architecture: A Primer for the Data Scientist

Over the past 5 years, the concept of big data has matured, data science has grown exponentially, and data architecture has become a standard part of organizational decision-making. Throughout all this change, the basic principles that shape the architecture of data have remained the same. There remains a need for people to take a look at the "bigger picture" and to understand where their data fit into the grand scheme of things. Data Architecture: A Primer for the Data Scientist, Second


Getting Started with Greenplum for Big Data Analytics

Getting Started with Greenplum for Big Data Analytics
  • Author : Sunila Gollapudi
  • Publisher : Packt Publishing Ltd
  • Release : 23 October 2013
GET THIS BOOKGetting Started with Greenplum for Big Data Analytics

Standard tutorial-based approach."Getting Started with Greenplum for Big Data" Analytics is great for data scientists and data analysts with a basic knowledge of Data Warehousing and Business Intelligence platforms who are new to Big Data and who are looking to get a good grounding in how to use the Greenplum Platform. It’s assumed that you will have some experience with database design and programming as well as be familiar with analytics tools like R and Weka.