Day 1 :

Introduction to Data Warehousing, Principles of Dimensional Modelling and Designing & Implementing the Time Dimension

By understanding the purpose and architecture of the data warehouse, and the main principles of the preferred dimensional modeling design technique, you will be better able to plan strategically as to your own data warehouse development projects.

Designing and Implementing the first Dimension, Time, will enable you to meet complex business requirements for analysis by date and time periods, in the most easy-to-use and effective way.

Day 2

Product & Customer Dimensions, Designing & Implementing Fact Tables, Designing & Implementing Aggregate Tables and Designing Multiple Fact Tables

Designing and Implementing Fact Tables, at base and summary level, will enable you to meet requirements for analysing different business metrics and key performance indicators with the optimum query performance. Understanding the reasons for Multiple Fact Tables, and looking at the most common types, will provide you with the means to meet more complex business reporting requirements.

Day 3

Implementing Multiple Fact Tables, Tracking History Design (1 & 2), Implementing Tracking History

By looking in detail at the various approaches to Tracking History on the data warehouse, you will better understand which technique to use in which circumstances. This will enable you to meet complex requirements for reporting consistently across time, despite the inevitable business changes that continually occur to your dimensions of analysis over extended time periods.

Day 4

Designing & Implementing Recursive Relationships, Dimensional Modelling Summary & Surgery and Further Advanced Design Techniques & Surgery

By examining the various approaches to meeting requirements to report against a recursive hierarchy, you will better appreciate the benefits and limitations of each technique, and therefore address such requirements in the most appropriate style for your data warehouse.

Day 4 summarises the main Dimensional Model design and implementation principles, goes through further important practical tips and tricks, and provides you with an opportunity to discuss in detail specific issues with your own environment. This will speed up the process of putting the learning into practice following the course, and help you determine immediate actions to carry out to move the data warehouse forward.

Day 5

Approach to Data Warehousing, Data Load & Data Quality Issues and End of Course Challenge

By looking at the overall data warehouse project approach, you will be better able to project plan the data warehouse phases, and the individual data mart builds, appreciating how the marts integrate into a high level design architecture. By considering data population and quality issues, you will be better able to reduce the project risks through appreciating the importance of a robust approach to resolving such issues.

The end of course challenge will provide you with an opportunity to consolidate your learning throughout the week, and therefore better prepare you for the challenges you will face implementing the data warehouse in your own environment.