Dimensional Modeling

Dimensional Modeling

This seminar will focus on the application of the data management principles required to model analytical data, such as in a data warehouse. It provides concrete guidelines, rules and examples for modeling this data. This is a shorter version of the 3 day class on data modeling for the data warehouse.

Objectives

Among the most important factors you will learn at this seminar will be how and when to apply dimensional considerations to a data warehouse
The seminar will teach how to effectively accomplish an optimized design of data, while ensuring the quality and integrity of the data warehouse data

What Attendees Will Learn

The overall data warehouse architecture

The Gather-Store-Deliver model

Kinds of data across this architecture

Kinds of reporting across this architecture

General methodology for building a data warehouse

MReview of dimensional modeling concepts

Definition of fact tables and dimensions

Is there such a thing as "dimensional modeling"?

The star and snowflake database schema

The pros and cons of each schema

Building the central data warehouse model

Comparison of operational and informational data

Data transformations from operational to analytical data

How to handle aggregates and summary data

The pros and cons of aggregates

Aggregates and restatement

How to model time and history

Types of changing data

Full and partial history

Conformed dimensions

When are conformed dimensions necessary

Qualities of conformed dimensions

How to avoid the need for conformed dimensions

Designing data marts

Types of data marts

Kinds of data by data mart

Optimizing Data Warehouse Design

Critical factors in data design

Data design compromises

Duration 1-2 days

Course Format Lecture and group discussion

Instructor Tom Haughey