Reeve A. Managing Data in Motion. Data Integration. Best Practice Techniques and Technologies

Издательство Morgan Kaufmann, 2013, -203 pp.Most organizations of middle to large size have hundreds or, more probably, thousands of applications, each with its own various databases and other data stores. Whether the data stores are from traditional technologies and database management systems, emerging technologies, or document management systems, it is critical to the usefulness of these applications to the organization that they share information between them. Developing and managing solutions for moving data between applications becomes an overwhelmingly complex problem unless addressed using a coordinated approach across an organization. This book describes a reasonable approach and architecture that enables managing the cacophony of interfaces in an application portfolio.
The focus of data management by information technology functions tends to be around the efficient management of data sitting in databases or persistent data that sits still. Since currently in most organizations applications are primarily purchased vendor solutions, managing the data that travels between systems, applications, data stores, and organizations— the data in motion— should be a central focus of information technology for any organization. Custom development in most organizations will continue to be more around the data traveling between applications than the development of new applications.Part 1 Introduction to Data Integration
The Importance of Data Integration
What Is Data Integration?
Types and Complexity of Data Integration
The Process of Data Integration Development
Part 2 Batch Data Integration
Introduction to Batch Data Integration
Extract, Transform, and Load
Data Warehousing
Data Conversion
Data Archiving
Batch Data Integration Architecture and Metadata
Part 3 Real Time Data Integration
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
Part 4 Big, Cloud, Virtual Data
Introduction to Big Data Integration
Cloud Architecture and Data Integration
Data Virtualization
Big Data Integration
Conclusion to Managing Data in Motion