Data Warehousing in the Age of Big Data (The Morgan Kaufmann Series on Business Intelligence)

__Data Warehousing in the Age of the Big Data__ will help you and your organization make the most of unstructured data with your existing data warehouse. As Big Data continues to revolutionize how we use data, it doesn't have to create more confusion. Expert author Krish Krishnan helps you make sense of how Big Data fits into the world of data warehousing in clear and concise detail. The book is presented in three distinct parts. Part 1 discusses Big Data, its technologies and use cases from early adopters. Part 2 addresses data warehousing, its shortcomings, and new architecture options, workloads, and integration techniques for Big Data and the data warehouse. Part 3 deals with data governance, data visualization, information life-cycle management, data scientists, and implementing a Big Data-ready data warehouse. Extensive appendixes include case studies from vendor implementations and a special segment on how we can build a healthcare information factory. Ultimately, this book will help you navigate through the complex layers of Big Data and data warehousing while providing you information on how to effectively think about using all these technologies and the architectures to design the next-generation data warehouse. * Learn how to leverage Big Data by effectively integrating it into your data warehouse. * Includes real-world examples and use cases that clearly demonstrate Hadoop, NoSQL, HBASE, Hive, and other Big Data technologies * Understand how to optimize and tune your current data warehouse infrastructure and integrate newer infrastructure matching data processing workloads and requirements

A comprehensive revision of the premier resource on master data management (MDM)

Master Data Management and Data Governance explains how to grow revenue, reduce administrative costs, and improve client retention by adopting a customer-focused business framework. The book consists of five major parts:
Part I introduces the set of the business problems and tactical and strategic challenges associated with MDM transformations and provides examples and guidance on industry-specific approaches to solutions.

Part II looks at the processes and technologies of designing and implementing solutions.
Part III examines MDM from the regulatory compliance, privacy, and security viewpoints.
Part IV discusses implementation issues including the scope and complexity of the testing and field deployment strategy. It also provides an overview of the marketplace, leading vendors, including IBM and Oracle, and their products and strategic directions.
Part V offers a high-level analysis of key strategic and tactical approaches of delivering an enterprise-wide holistic business and technology initiative.



Master Data Management and Data Governance covers:

• Major MDM data domains and MDM applications by industry

• Evolution of MDM architecture

• Data modeling and management concerns of MDM architecture

• Architecting for entity and relationships resolution

• Analytical and operational MDM



Full details on MDM

Introduction to Master Data Management and Customer Data Integration; MDM: Overview of Market Drivers and Key Challenges; MDM Applications by Industry; Architectural Considerations; MDM Architecture Classification, Concepts, Principles and Components; Data Management Concerns of MDM Architecture: Entities, Hierarchies and Metadata; MDM Services for Entity and Relationships Resolution and Hierarchy Management; Master Data Modeling; Data Security, Privacy and Regulatory Compliance; Overview of Risk Management for Master Data; Introduction to Information Security and Identity Management; Protecting Content for Secure Master Data Management; Enterprise Security and Data Visibility in Master Data; Implementing and Governing Master Data Management; Building Business Case and Defining Data Governance Framework for MDM; Project Initiation; Identification, Matching, Aggregation and Holistic View of the Master Objects; Beyond Party Match: Merge, Split, Groups and Relationships; Data Synchronization and Integration Styles; Data Governance: Frameworks, Information Quality Processes and Metrics; Additional Implementation Considerations; Master Data Management: Market, Trends and Directions; MDM Roadmap; Regulations and Compliance Rules Impacting Master Data Management Projects

The latest techniques for building a customer-focused enterprise environment'The authors have appreciated that MDM is a complex multidimensional area, and have set out to cover each of these dimensions in sufficient detail to provide adequate practical guidance to anyone implementing MDM. While this necessarily makes the book rather long, it means that the authors achieve a comprehensive treatment of MDM that is lacking in previous works.'-- Malcolm Chisholm, Ph.D., President, AskGet.com Consulting, Inc. Regain control of your master data and maintain a master-entity-centric enterprise data framework using the detailed information in this authoritative guide. Master Data Management and Data Governance, Second Edition provides up-to-date coverage of the most current architecture and technology views and system development and management methods. Discover how to construct an MDM business case and roadmap, build accurate models, deploy data hubs, and implement layered security policies. Legacy system integration, cross-industry challenges, and regulatory compliance are also covered in this comprehensive volume. Plan and implement enterprise-scale MDM and Data Governance solutions Develop master data model Identify, match, and link master records for various domains through entity resolution Improve efficiency and maximize integration using SOA and Web services Ensure compliance with local, state, federal, and international regulations Handle security using authentication, authorization, roles, entitlements, and encryption Defend against identity theft, data compromise, spyware attack, and worm infection Synchronize components and test data quality and system performance

Data Warehousing in the Age of the Big Data will help you and your organization make the most of unstructured data with your existing data warehouse.

As Big Data continues to revolutionize how we use data, it doesn't have to create more confusion. Expert author Krish Krishnan helps you make sense of how Big Data fits into the world of data warehousing in clear and concise detail. The book is presented in three distinct parts. Part 1 discusses Big Data, its technologies and use cases from early adopters. Part 2 addresses data warehousing, its shortcomings, and new architecture options, workloads, and integration techniques for Big Data and the data warehouse. Part 3 deals with data governance, data visualization, information life-cycle management, data scientists, and implementing a Big Data–ready data warehouse. Extensive appendixes include case studies from vendor implementations and a special segment on how we can build a healthcare information factory.

Ultimately, this book will help you navigate through the complex layers of Big Data and data warehousing while providing you information on how to effectively think about using all these technologies and the architectures to design the next-generation data warehouse.

• Learn how to leverage Big Data by effectively integrating it into your data warehouse.
• Includes real-world examples and use cases that clearly demonstrate Hadoop, NoSQL, HBASE, Hive, and other Big Data technologies
• Understand how to optimize and tune your current data warehouse infrastructure and integrate newer infrastructure matching data processing workloads and requirements

"In conclusion as you come to the end of this book, the concept of a Data Warehouse and its primary goal of serving the enterprise version of truth, and being the single platform for all the source of information will continue to remain intact and valid for many years to come. As we have discussed across many chapters and in many case studies, the limitations that existed with the infrastructures to create, manage and deploy Data Warehouses have been largely eliminated with the availability of Big Data technologies and infrastructure platforms, making the goal of the single version of truth a feasible reality. Integrating and extending Big Data into the Data Warehouse, and creating a larger decision support platform will benefit businesses for years to come. This book has touched upon governance and information lifecycle management aspects of Big Data in the larger program, however you can reuse all the current program management techniques that you follow for the Data Warehouse for this program and even implement agile approaches to integrating and managing data in the Data Warehouse. Technologies will continue to evolve in this spectrum and there will be more additions of solutions, which can be integrated if you follow the modular integration approaches to building and managing the Data Warehouse. The Appendix sections contain many more case studies and a special section on Healthcare Information Factory based on Big Data approaches. These are more guiding posts to help you align your thoughts and goals to building and integrating Big Data in your Data Warehouse"-- Provided by publisher. 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 and executing an MDM project that leads to measurable improvements in business productivity and effectiveness.

* Presents a comprehensive roadmap that you can adapt to any MDM project.
* Emphasizes the critical goal of maintaining and improving data quality.
* Provides guidelines for determining which data to “master.”
* Examines special issues relating to master data metadata.
* Considers a range of MDM architectural styles.
* Covers the synchronization of master data across the application infrastructure. 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 and executing an MDM project that leads to measurable improvements in business productivity and effectiveness. * Presents a comprehensive roadmap that you can adapt to any MDM project. * Emphasizes the critical goal of maintaining and improving data quality. * Provides guidelines for determining which data to "master." * Examines special issues relating to master data metadata. * Considers a range of MDM architectural styles. * Covers the synchronization of master data across the application infrastructure Everything you ever wanted to know about growing grapes March and Simon's Organizations has become a classic in the field of organizational management for its broad scope and depth of information. Written by two of the most prominent experts in the field, this book offers invaluable insight on all aspects of organizational culture through deep discussion of organization theory. The definitive reference for topics including bounded rationality, satisficing, inducement/contribution balances, attention focus, uncertainty absorption and more, this seminal text offers authoritative insight with a practical grounding in the field. "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 and executing an MDM project that leads to measurable improvements in business productivity and effectiveness."--Jacket Master data and master data management Coordination, stakeholders, requirements, and planning Components and the maturity model Data governance for master data management Data quality and MDM Metadata management for MDM Identifying master metadata and master data Data modeling for MDM Paradigms and architectures Data consolidation and integration Master data synchronization And the functional services layer Management guidance for MDM. This new edition incorporates a new introduction which places the material in its contemporary context, whilst still preserving the 1958 text. It examines such concepts as bounded rationality, satisficing, inducement/contribution balances, problem solving and uncertainty absorption. This comprehensive revision of the premier resource on master data management (MDM) provides a common framework for the understanding and implementation of MDM initiatives.

This book provides the original and definitive treatments of such fundamental concepts as bounded rationality, attention focus, and problem solving.