Course Length - 3 Days

Description
This course considers how to build, implement, tune and utilize data warehouses with Oracle technology. Logical data warehouse concepts are considered such as dimension tables, fact tables and star schemas. Implementing such logical concepts using the Oracle database is then presented including defining dimensions, hierarchies, measures and other objects. Physical implementation techniques are considered such as bitmap indexes, materialized views, and others. Emphasis is placed on the parallel execution features of the database and how these can yield significant performance advantages.

Course Objectives
This course highlights the features within the Oracle database specifically intended to support data warehouses and data mining operations. One must use these specialized features to initially implement the data warehouse and thereafter utilize yet other features to administer and manage this unique environment. Due to the enormous volume of data often contained within data warehouses, a proper understanding of these features is essential. Among the specific objectives of this course are:
• Understanding star and snowflake schemas and other data warehouse physical and logical database objects.
• Understanding and encouraging optimization of star queries.
• Creating and maintaining materialized views to enhance ad-hoc query performance against enormous volumes of transactional data.
• Manage materialized views to effectively and efficiently maintain their structure over the course of time.
• Creating and maintaining dimensions and hierarchies to enhance ad-hoc query performance and support sophisticated data mining.
• Performing dimensional analysis of data warehouse information and building cubes.
• Discuss and demonstrate options for building Extraction, Transformation and Transformation (ETT) or Loading (ETL) processes.