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Print PageOracle 9i Data Warehouse Administration
Description:
This course condiders 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".
View other Oracle Courses available
View other Oracle Courses available
- Cost: Price on application
- Duration: 5 Days
- This course is not available as part of our public schedule but can be provided on a customised client specific basis.
Prerequisites:
Introduction to Oracle 9i: SQL
Introduction to Oracle 9i: PL/SQL Language
Introduction to Oracle 9i: Advanced 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
Contrast OLTP & Warehouse Databases
Using Materialised Views:
Enable Materialised Views & Query Rewrite
Create the Materialised View
Create the Materialised View
Maintaining Materialised Views:
Maintenance Options
About the Types of Views
Altering and Dropping Views
Data Dictionary Storage
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
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
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
Utilizing Constraints with Query Rewrite
Query Rewrite Integrity Levels
Query Rewrite Influences
Dimensions:
Creating & Maintaining Dimensions
Data Dictionary Storage
Dimension System-Supplied Packages
Data Dictionary Storage
Dimension System-Supplied Packages
The Summary Advisor Tool:
The DBMS_OLAP() Package
Incorporating Workload Statistics
OEM Summary Advisor Wizard
Incorporating Workload Statistics
OEM Summary Advisor Wizard
Dimensional Analysis of Data:
Data Sampling Techniques
Aggregation Techniques
Building the Data Warehouse Cube
Aggregation Techniques
Building the Data Warehouse Cube
An Introduction to the Analytic Functions:
Ranking Functions
Understanding Function Execution
Understanding Function Execution
Incorporating Bitmap Indexes :
Star Queries & the Optimizer:
A Star Transormation Scenario
Encouraging Star Transformation
Encouraging Star Transformation
ETT Features (External Tables):
Creating & Accessing External Tables
Performance Considerations
Viewing & Altering Properties of External Tables
Performance Considerations
Viewing & Altering Properties of External Tables
ETT Features (Table Functions):
Implementing a Pipelined Table Function