Dimensional Modeling Workshop

PT10316
Summary
This 3-day course introduces students to best industry practices for designing data warehouse (DW) data structures and databases. This workshop has previously been called, "Data Modeling for the Data Warehouse."Data models are a blueprint for the information requirements of an organization. They are critical to understanding data in the analytical environment of the data warehouse. Without a data model, the understanding, implementation and maintenance of the data warehouse are difficult, if not impossible. Analytical data modeling, such as one sees in the data warehouse, presents new requirements, issues, and challenges from those of the traditional OLTP environment.When first modeling for the data warehouse, even the most experienced of applications data modelers and database designers can falter over these challenges. They can even make critical errors in design. The reason is that the data warehouse requires different roles and uses of data, a different use of normalization, and new modeling constructs. Key special requirements of the data warehouse focus on time, location, and dimensional aspects of data. These requirements are among the reasons that analytical data modeling demands different skills, perspectives and techniques.This workshop focuses on where data models fit into the data warehouse development process. It provides the skills required and techniques necessary to produce the data models. It shows how to use data to implement and maintain a data warehouse. In addition, modeling data warehouses presents new data design challenges. The major factors to consider in data warehouse database design are: data size and complexity; query composition and complexity; query load; and query concurrency. Technology also plays a role. Evaluation of these factors will result in different database designs. Analytical modeling constructs that support time, location, dimensionality and redundancy require that even experienced data modelers and database designer need to learn new skills.
Prerequisites
Before taking this course, students should have taken an "Introduction To Data Warehousing" or have equivalent knowledge. Students should also have an understanding of data modeling, especially entity-relationship modeling.
Duration
3 Days/Lecture & Lab
Audience
This course is ideal for:Developers and administrators involved in data warehousingBusiness and technical data warehouse team members
Topics
  • Introduction to Data Warehousing
  • Dimensional Modeling
  • Building the DW Model
  • Data Warehouse Architectures
  • Information Gathering
  • Building the Central DW Model
  • Modeling Aggregates
  • Modeling Time and History
  • Building Data Marts
  • Optimizing the DW Design
  • Data Warehouse Technology
  • Summary and Conclusion
  • Case Studies
  • Glossary

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