PRINT
PDF
WORD
CSV
EXCEL
Moocable is learner-supported. When you buy through links on our site, we may earn an affiliate commission.
Data Integration Blueprint and Modeling: Techniques for a Scalable and Sustainable Architecture
via IBM Press
Description
Making Data Integration Work: How to
Systematically Reduce Cost, Improve Quality, and Enhance
Effectiveness Today’s enterprises are investing
massive resources in data integration. Many possess thousands of
point-to-point data integration applications that are costly,
undocumented, and difficult to maintain. Data integration now
accounts for a major part of the expense and risk of typical data
warehousing and business intelligence projects--and, as businesses
increasingly rely on analytics, the need for a blueprint for data
integration is increasing now more than ever. This book presents the solution: a clear,
consistent approach to defining, designing, and building data
integration components to reduce cost, simplify management, enhance
quality, and improve effectiveness. Leading IBM data management
expert Tony Giordano brings together best practices for
architecture, design, and methodology, and shows how to do the
disciplined work of getting data integration right. Mr. Giordano begins with an overview of the
“patterns” of data integration, showing how to build
blueprints that smoothly handle both operational and analytic data
integration. Next, he walks through the entire project lifecycle,
explaining each phase, activity, task, and deliverable through a
complete case study. Finally, he shows how to integrate data
integration with other information management disciplines, from
data governance to metadata. The book’s appendices bring
together key principles, detailed models, and a complete data
integration glossary. Coverage includes
Implementing repeatable, efficient, and
well-documented processes for integrating data
Lowering costs and improving quality by
eliminating unnecessary or duplicative data integrations
Managing the high levels of complexity
associated with integrating business and technical data
Using intuitive graphical design
techniques for more effective process and data integration
modeling
Building end-to-end data integration
applications that bring together many complex data sources
Books
IBM Press
Exclusively Paid 
8h 58m 
No Certificate 
416 pages Data Integration Blueprint and Modeling: Techniques for a Scalable and Sustainable Architecture
via IBM Press
Affiliate notice
Making Data Integration Work: How to Systematically Reduce Cost, Improve Quality, and Enhance Effectiveness
Today’s enterprises are investing massive resources in data integration. Many possess thousands of point-to-point data integration applications that are costly, undocumented, and difficult to maintain. Data integration now accounts for a major part of the expense and risk of typical data warehousing and business intelligence projects--and, as businesses increasingly rely on analytics, the need for a blueprint for data integration is increasing now more than ever.
This book presents the solution: a clear, consistent approach to defining, designing, and building data integration components to reduce cost, simplify management, enhance quality, and improve effectiveness. Leading IBM data management expert Tony Giordano brings together best practices for architecture, design, and methodology, and shows how to do the disciplined work of getting data integration right.
Mr. Giordano begins with an overview of the “patterns” of data integration, showing how to build blueprints that smoothly handle both operational and analytic data integration. Next, he walks through the entire project lifecycle, explaining each phase, activity, task, and deliverable through a complete case study. Finally, he shows how to integrate data integration with other information management disciplines, from data governance to metadata. The book’s appendices bring together key principles, detailed models, and a complete data integration glossary.
Coverage includes
Implementing repeatable, efficient, and well-documented processes for integrating data
Lowering costs and improving quality by eliminating unnecessary or duplicative data integrations
Managing the high levels of complexity associated with integrating business and technical data
Using intuitive graphical design techniques for more effective process and data integration modeling
Building end-to-end data integration applications that bring together many complex data sources
Loading...
Saving...
Loading...