Managing Data in Motion: Data Integration Best Practice Techniques and Technologies

  • 3h 10m
  • April Reeve
  • Elsevier Science and Technology Books, Inc.
  • 2013

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 hundreds to thousands computer systems that have been built, purchased, and acquired over time. The data from these various systems needs to be integrated for reporting and analysis, shared for business transaction processing, and converted from one format to another when old systems are replaced and new systems are acquired.

The management of the "data in motion" in organizations is rapidly becoming one of the biggest concerns for business and IT management. Data warehousing and conversion, real-time data integration, and cloud and "big data" applications are just a few of the challenges facing organizations and businesses today. Managing Data in Motion tackles these and other topics in a style easily understood by business and IT managers as well as programmers and architects.

  • Presents a vendor-neutral overview of the different technologies and techniques for moving data between computer systems including the emerging solutions for unstructured as well as structured data types
  • Explains, in non-technical terms, the architecture and components required to perform data integration
  • Describes how to reduce the complexity of managing system interfaces and enable a scalable data architecture that can handle the dimensions of "Big Data"

About the Author

April Reeve has spent the last 25 years working as an enterprise architect and program manager in the financial services and health sciences industries. Currently she is working for EMC Consulting in the Enterprise Information Management practice. April is an expert in multiple Data Management disciplines including Data Conversion, Data Warehousing, Business Intelligence, Master Data Management, Data Integration, and Data Governance.

In this Book

  • Foreword
  • Introduction
  • The Importance of Data Integration
  • What is Data Integration?
  • Types and Complexity of Data Integration
  • The Process of Data Integration Development
  • Introduction to Batch Data Integration
  • Extract, Transform, and Load
  • Data Warehousing
  • Data Conversion
  • Data Archiving
  • Batch Data Integration Architecture and Metadata
  • Introduction to Real-Time Data Integration
  • Data Integration Patterns
  • Core Real-Time Data Integration Technologies
  • Data Integration Modeling
  • Master Data Management
  • Data Warehousing with Real-Time Updates
  • Real-Time Data Integration Architecture and Metadata
  • Introduction to Big Data Integration
  • Cloud Architecture and Data Integration
  • Data Virtualization
  • Big Data Integration
  • Conclusion to Managing Data in Motion
  • References
SHOW MORE
FREE ACCESS

YOU MIGHT ALSO LIKE

Audiobook Data Mesh in Action
Course Business Transformation Through IT: Cloud Computing for Decision Makers
Rating 4.6 of 58 users Rating 4.6 of 58 users (58)
Book The Enterprise Big Data Framework: Building Critical Capabilities to Win in the Data Economy