What this book is about and why it’s necessary
What the reader will learn
Who should read this book
How this book is organized
Part 1: Introduction to data integration
Part 2: Batch data integration
Part 3: Real-time data integration
Part 4: Big data integration
Part 1: Introduction to Data Integration
Chapter 1. The Importance of Data Integration
The natural complexity of data interfaces
The rise of purchased vendor packages
Key enablement of big data and virtualization
Chapter 2. What Is Data Integration?
Data in motion
Integrating into a common format—transforming data
Migrating data from one system to another
Moving data around the organization
Pulling information from unstructured data
Moving process to data
Chapter 3. Types and Complexity of Data Integration
The differences and similarities in managing data in motion and persistent data
Batch data integration
Real-time data integration
Big data integration
Chapter 4. The Process of Data Integration Development
The data integration development life cycle
Inclusion of business knowledge and expertise
Part 2: Batch Data Integration
Chapter 5. Introduction to Batch Data Integration
What is batch data integration?
Batch data integration life cycle
Chapter 6. Extract, Transform, and Load
What is ETL?
Chapter 7. Data Warehousing
What is data warehousing?
Layers in an enterprise data warehouse architecture
Types of data to load in a data warehouse
Chapter 8. Data Conversion
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"
Data Warehouse Professionals; Data Modelers and Architects; Database and Network Administrators; ETL and Application Programmers; Project Managers; IT and Data Center Managers; CIO/CTO
- No. of pages:
- © Morgan Kaufmann 2013
- 15th March 2013
- Morgan Kaufmann
- eBook ISBN:
- Paperback ISBN:
"The highlight of the book is that the author is able to present a broad, complicated subject in a coherent, consolidated, and readable manner. This is ideal for busy information technology managers and chief technical officers who have little time for outside reading. The book is especially valuable for those managers who are not familiar with modern data management or who are fluent in general computing technology but are tasked with managing data on a larger scale."--ComputingReviews.com, November 4, 2013
"Reeve, an enterprise information consultant with EMC, describes different techniques, technologies, and best practices for managing the transfer of data between computer systems and integrating disparate databases together within a large organization."--Reference and Research Book News, August 2013
"Few if any enterprises have the luxury of a single unified integrated data platform. Yet one of the least considered areas in enterprise information management is how we should treat and manage the growing numbers of interfaces. April Reeve presents a much-needed overview and guide to the challenges of data integration."--John Ladley, Principal of IMCue Solutions, Editor of the Data Strategy Journal
April Reeve has spent the last 25 years working as an enterprise architect and program manager, primarily for large financial services firms. Currently she is working for EMC Consulting as a Business Consultant 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. She is a regular speaker on Data Management topics at Industry conferences.
April Reeve is a Business Consultant in the Enterprise Information Management practice at EMC Consulting