Data Modeling for Warehouse

Data Modeling for the Data Warehouse

This course introduces students to best industry practices for designing data warehouse data structures and databases.

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. 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 mean that even experienced data modelers and database designer need to learn new skills.

Objectives

Understand and apply the concepts and principles of data warehousing
Understand and apply basic data warehouse architectures and development processes
Understand and apply basic data warehouse data design techniques
Ensure that business requirements are identified and included in your design
Gather, organize and prioritize business requirements
Choose between an appropriately normalized data model or a more dimensionalized model
Understand how and when to use aggregation
Understand and apply different modeling techniques for different data warehouse structures
Understand how to model time and history
Understand how to optimize the data warehouse design
Learn categories of warehouse tools and technology

Duration 2-3 days

Who Should Attend

Developers and administrators involved in data warehousing
Business and technical data warehouse team members

Prerequesite

Our “Introduction To Data Warehousing” or equivalent knowledge
An understanding of data modeling, especially entity-relationship modeling

Who Should Not Attend

Those who have already attended our “Designing the Data Warehouse

Course format Lecture, group discussion and exercises

Instructor Tom Haughey