Course details
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, partitioned tables, materialized views, and others. Emphasis is placed on the parallel execution features of the database and how these can yield significant performance advantages. This course was formerly called "Build Oracle 9i Data Warehouses".
Prerequisites:
- Introduction to Oracle 9i: SQL
- Introduction to Oracle 9i: PL/SQL Language
- Introduction to Oracle 9i: Advanced SQL
About Data Warehousing:
- Understanding Warehouse Concepts and Terms
- Contrast OLTP & Warehouse Databases
Using Materialised Views:
- Enable Materialised Views & Query Rewrite
- Create the Materialised View
Maintaining Materialised Views:
- Maintenance Options
- About the Types of Views
- Altering and Dropping Views
- Data Dictionary Storage
Refreshing Materialised Views:
- Specifying the Default Refresh Options
- Performing a Refresh on Demand
- Implementing Fast Refresh
Monitor Query Rewrite with Explain Plan:
- Generating the Execution Plan
- Viewing the Execution Plan
- Interpreting the Execution Plan
Controlling the Query Rewrite Facility:
- Query Rewrite Optimiser Hints
- Utilizing Constraints with Query Rewrite
- Query Rewrite Integrity Levels
- Query Rewrite Influences
Dimensions:
- Creating & Maintaining Dimensions
- Data Dictionary Storage
- Dimension System-Supplied Packages
The Summary Advisor Tool:
- The DBMS_OLAP() Package
- Incorporating Workload Statistics
- OEM Summary Advisor Wizard
Dimensional Analysis of Data:
- Data Sampling Techniques
- Aggregation Techniques
- Building the Data Warehouse Cube
An Introduction to the Analytic Functions:
- Ranking Functions
- Understanding Function Execution
Incorporating Bitmap Indexes :
Star Queries & the Optimizer:
- A Star Transormation Scenario
- Encouraging Star Transformation
ETT Features (External Tables):
- Creating & Accessing External Tables
- Performance Considerations
- Viewing & Altering Properties of External Tables
ETT Features (Table Functions):
- Implementing a Pipelined Table Function
Course Location
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