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Managing Data in Motion

Data Integration Best Practice Techniques and Technologies

By
  • April Reeve, April Reeve is a Business Consultant in the Enterprise Information Management practice at EMC Consulting

Managing Data in Motion includes the techniques that have been developed for significantly reducing the complexity of managing system interfaces and enabling a scalable data architecture. Author April Reeve brings over two decades of experience to present a vendor-neutral approach that can be understood by IT and business managers as well as programmers and architects.Learn the different techniques, technologies, and best practices used to manage the passing of data between computer systems and integrating disparate data together in an enterprise environment.

Audience
Data Warehouse Professionals; Data Modelers and Architects; Database and Network Administrators; ETL and Application Programmers; Project Managers; IT and Data Center Managers; CIO/CTO

Paperback, 230 Pages

Published: March 2013

Imprint: Morgan Kaufmann

ISBN: 978-0-12-397167-8

Contents

  • Part 1: Introduction

    • An Explosion of New Technologies for Managing the Movement and Integration of Big Data, Cloud Processing, and Virtual Data

    • The Importance of Data Integration in Data and Application Management

    • The Differences and Similarities in Managing Data in Motion and Persistant Data

    • Types and Complexity of Data Integration

    Part 2: Batch Data Integration

    • Extract, Transformation, and Load 

    • Data Warehousing

    • Data Conversion

    • Data Archiving

    • Batch Data Integration Architecture and Metadata

    Part 3: Real-Time Data Integration

    • Data Integration Patterns

    • Enterprise Service Bus (ESB)

    • Service Oriented Architecture (SOA)

    • Extensible Markup Language (XML) and other formats

    • Data Replication

    • Modeling

    • Master Data Management

    • Data Warehousing with Real Time Updates

    • Real Time Data Integration Architecture and Metadata

    • Interactions with Legacy Systems

    • External Interaction

    Part 4: Cloud and Big Data Integration

    • Cloud Architecture and Data Integration

    • Big Data Integration

    • Data Virtualization

    • In-Memory Data

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