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Course Schedule:
Virtual Classroom	07/18-07/20
Toronto, ON	07/18-07/20
Vancouver, BC	07/18-07/20
Calgary, AB	07/18-07/20
Reston, VA	07/18-07/20
Chicago, IL	07/18-07/20
Columbus, OH	07/18-07/20
Baltimore, MD	07/18-07/20
Columbia, MD	07/18-07/20
Annapolis, MD	07/18-07/20
Wash Metro Area, DC	07/18-07/20
Richmond, VA	07/18-07/20
Norfolk, VA	07/18-07/20
Denver, CO	07/18-07/20
Los Angeles, CA	07/18-07/20
San Francisco, CA	07/18-07/20
Indianapolis, IN	07/18-07/20
Boston, MA	07/18-07/20
Des Moines, IA	07/18-07/20
Cedar Rapids, IA	07/18-07/20
Minneapolis-St Paul, MN	07/18-07/20
St Louis, MO	07/18-07/20
Seattle, WA	07/18-07/20
Philadelphia, PA	07/18-07/20
Detroit, MI	07/18-07/20
Phoenix, AZ	07/18-07/20
Tucson, AZ	07/18-07/20
Milwaukee, WI	07/18-07/20
Charleston, WV	07/18-07/20
Atlanta, GA	07/18-07/20
Raleigh-Durham, NC	07/18-07/20
Toronto, ON	09/26-09/28
Vancouver, BC	09/26-09/28
Calgary, AB	09/26-09/28
Virtual Classroom	09/26-09/28
Reston, VA	09/26-09/28
Chicago, IL	09/26-09/28
Columbus, OH	09/26-09/28
Baltimore, MD	09/26-09/28
Columbia, MD	09/26-09/28
Annapolis, MD	09/26-09/28
Wash Metro Area, DC	09/26-09/28
Richmond, VA	09/26-09/28
Norfolk, VA	09/26-09/28
Denver, CO	09/26-09/28
Los Angeles, CA	09/26-09/28
San Francisco, CA	09/26-09/28
Indianapolis, IN	09/26-09/28
Boston, MA	09/26-09/28
Des Moines, IA	09/26-09/28
Cedar Rapids, IA	09/26-09/28
Minneapolis-St Paul, MN	09/26-09/28
St Louis, MO	09/26-09/28
Seattle, WA	09/26-09/28
Philadelphia, PA	09/26-09/28
Detroit, MI	09/26-09/28
Phoenix, AZ	09/26-09/28
Tucson, AZ	09/26-09/28
Milwaukee, WI	09/26-09/28
Charleston, WV	09/26-09/28
Atlanta, GA	09/26-09/28
Raleigh-Durham, NC	09/26-09/28
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Designing the Data Warehouse

Summary:
This workshop will stress that designing a data warehouse is not just an intuitive process based solely on the spontaneous judgment of a skilled analyst. It can be based on sound rules and guidelines just as production data models are.

Duration:
3 Days/Lecture & Lab

Topics:

Workshop Agenda
Introduction to Data Warehousing
Data Warehouse Methodology
Introduction To Data Modeling
Building the Data Warehouse Model
Levels of Data In the Enterprise
Derived Data
Modeling Time and History
Information Gathering
Analyzing Current Systems Data
Data Transformations
Critical Warehouse Components
Optimizing the Data Warehouse Design
Data Warehouse Technology
Important Considerations and Issues
Managing Data Warehouse Projects
Summary and Conclusion
Case Studies

Last Update: May 21, 2012

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Designing the Data Warehouse