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ORA03DAW-9i-01-SG
Oracle 9i Data Warehouse Administration (5 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, 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 “Building Oracle 9i Data Warehouses”.
Audience
Target audience for this course is database administrators, data warehouse administrators and application developers who will be responsible for implementing and using data warehouse technology.
Mandatory Prerequisites
• The Sideris course Introduction to Oracle 9i: SQL
• The Sideris course Introduction to Oracle 9i: PL/SQL Language
• The Sideris course Introduction to Oracle 9i: Advanced SQL
Additional Recommended Prerequisites
In addition, the following Sideris courses are strongly recommended, although not mandatory, prerequisites:
• The Sideris course Oracle 9i Architecture For Developers
• The Sideris course Oracle 9i New & Advanced Features for Developers
• The Sideris course Oracle 9i SQL Tuning
OR
• The Sideris course Oracle 9i Database: Administration – DBA I
• The Sideris course Oracle 9i New & Advanced Features for DBAs
• The Sideris course Oracle 9i SQL Tuning
Suggested Next Courses
• The Sideris course Oracle 9i Discoverer For Power Users
Objectives
The objective of this course is to consider present a comprehensive consideration of data warehouse features which exist within the Oracle database. Major subject areas to be explored are:
• Understanding star schemas and other data warehouse objects.
• Understanding and encouraging optimization of star queries.
• Creating and maintaining materialized views to enhance ad-hoc query performance.
• Creating and maintaining dimensions to enhance ad-hoc query performance.
• Performing dimensional analysis of data warehouse information.
• Using the Summary Advisor tool for data warehouse design recommendations.
Course Outline
ABOUT DATA WAREHOUSING • UNDERSTANDING WAREHOUSE CONCEPTS & TERMS • CONTRAST OLTP & WAREHOUSE DATABASES
USING MATERIALIZED VIEWS • ENABLE MATERIALIZED VIEWS & QUERY REWRITE • CREATE THE MATERIALIZED VIEW
MAINTAINING MATERIALIZED VIEWS • MAINTENANCE OPTIONS • ABOUT THE TYPES OF VIEWS • ALTERING AND DROPPING VIEWS • DATA DICTIONARY STORAGE
REFRESHING MATERIALIZED 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 OPTIMIZER 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 TRANSFORMATION 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
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