Oracle Training Oracle Support Development Oracle Apps

 E-mail Us
 Oracle Articles
New Oracle Articles

 Oracle Training
 Oracle Tips

 Oracle Forum
 Class Catalog

 Remote DBA
 Oracle Tuning
 Emergency 911
 RAC Support
 Apps Support
 Oracle Support

 SQL Tuning

 Oracle UNIX
 Oracle Linux
 Remote s
 Remote plans
 Application Server

 Oracle Forms
 Oracle Portal
 App Upgrades
 SQL Server
 Oracle Concepts
 Software Support

 Remote S


 Consulting Staff
 Consulting Prices
 Help Wanted!


 Oracle Posters
 Oracle Books

 Oracle Scripts

Don Burleson Blog 







Managing an Oracle Data Warehouse

© 2007-2016 by Burleson Corporation

This course is taught at your Company site with up to 20 students. 

Click here for on-site course prices



Key Features

* Understand the evolution of decision support systems to data warehouse.

* Gain intimate knowledge of data - MYCIN.

* Employ parallel processors and terabyte storage.

* See examples of MPP data warehouses (Mead Data Central).

* Understand referential integrity and data cleansing.

* See past the marketing hype.


Course Description

This two-day Oracle Data Warehouse training is designed to give the student a firm conceptual understanding of the goals and techniques that are used in a data warehouse. The Oracle Data Warehouse class explains the concepts and techniques in plain English, and strips away all of the marketing hype to give the student a clear understanding of how to construct a data warehouse using the new technologies. The seminar begins with a historical review of data warehousing and explains the basic construction techniques for data warehousing and contrasts them with traditional online teleprocessing systems.

The student will leave this seminar with an understanding of data warehouse design techniques for relational databases, including STAR schema design, the pre-aggregation of data, and online analytical processing (OLAP). In addition, the student will understand multidimensional databases, and be able to understand how they are created and maintained. This seminar also introduces data warehouse "front-ends" for relational OLTP engines and explains how these tools are used in real-world situations. Lastly, the student is exposed to the data warehouse development life cycle where they will understand data extraction, data cleansing, metadata repositories, and practical tips for insuring a successful warehouse project.

Book Required

  • N/A


This course is designed for the working Oracle professional and the amount of previous experience with Oracle is incidental.
Previous experience with relational database management and SQL is helpful, but this class is self-contained and has no formal prerequisites.

Curriculum Design

This course was designed by Donald K. Burleson, an acknowledged leader in Oracle database administration.  Burleson was chosen by Oracle Press to write the authorized edition of Oracle High-Performance SQL tuning.  Burleson Corporation instructors offer decades of real world DBA experience in Oracle features, and they will share their Oracle secrets in this intense Oracle data warehouse training.

Managing a Data Warehouse

Don Burleson


Day One

9:00 - 10:00 The evolution of decision support systems to data warehouse

DSS vs. Expert systems

The DSS evolution

intimate knowledge of data - MYCIN

support ad-hoc ("what if") queries

seamless access to distributed data

interactive in nature

either fully-structured or semi-structured queries

non-procedural queries ("show me more like this")

start at summarized level & drill-down into detail

GUI for visual presentation

IBM vs. Bill Inmon - evolution of the data warehouse

The new business environment

fast reaction to market changes

large volumes of non-fielded data

terabytes of legacy data - those who forget the past are condemned to repeat it

the "invention" of OLAP

10:00-10:15 BREAK


10:15 - 11:00 Multi-dimensional databases - information systems for decision support

pivot tables - three dimensional data (PC-BASED DEMO)

differing levels of summarization

11:00 - 11:30 Data mining - Conceptual overview

parallel processors and terabyte storage.

hands-off analysis - identification of unobtrusive trends within data

Intelligent agents - used to identify trends based on "hints" from users.

linear regression example - trumpet of doom

11:30 - 1:00 LUNCH

1:00 - 2:00 Hardware & Software advances with data warehousing

Parallel processing hardware

MPP& SMP architectures

Examples of MPP data warehouses (Mead Data Central)

Software advances

AI-based query engines (ConQuest, Folio, Fulcrum)

Parallel database software

multi-dimensional databases (Essbase)

Enterprise computing architectures

common query languages - SQL wrappers UniFace EDA/SQL

data warehouse tools - Prism, Vality

2:00 - 2:15 Break


2:15 - 3:30 Introduction to data warehouse design

Data collection analysis

STAR schema design

de-normalization - pre-joining tables

The Role of Metadata

Why is metadata important? (changed procedures, usage)

What are the current metadata tools?

How to choose/create a metadata repository

3:30-3:45 BREAK

3:45-4:30 Pre-aggregating relational data for relational warehouses



Day Two

9:00-9:45 Exercise review

9:45-10:30 Populating the data warehouse:

Data-driven vs. application-driven design

Data is collected into a data-driven design

Keeping the warehouse current

Asynchronous updating strategies

Data extraction and cleansing

Extracting from the warehouse Slicing the data warehouse - operational

"views" across functional areas vs. functional slices.

Process mgt. for staging, population, and slicing data

Referential integrity and data cleansing

Enforcing business rules across diverse systems

Sizing the Data Warehouse

Estimation of initial sizes

Relational determination

Sizing for non-relational inputs

Forecasting future size requirements

Rolling/archiving of obsolete data

10:30-10:45 BREAK

10:45-11:30 Data Warehouse development life cycle

The feasibility study - cost/benefit analysis

the issue of intangibles

The black-hole argument

The pilot study

survey existing applications

review external data sources

Marketing the project

packaging the warehouse

training on data warehouse usage


Implementation Hints

New Trends - Data Marts, Data Trolling

Evaluating warehouse tools & products

Seeing past the marketing hype

Key elements to look for in a product

Market share

User success stories

Robust functionality/extensibility

11:30-1:00 LUNCH

2:30-5:00 Site-specific data warehouse issues

Open discussion - Bring your questions/issues


Burleson is the American Team

Note: This Oracle documentation was created as a support and Oracle training reference for use by our DBA performance tuning consulting professionals.  Feel free to ask questions on our Oracle forum.

Verify experience! Anyone considering using the services of an Oracle support expert should independently investigate their credentials and experience, and not rely on advertisements and self-proclaimed expertise. All legitimate Oracle experts publish their Oracle qualifications.

Errata?  Oracle technology is changing and we strive to update our BC Oracle support information.  If you find an error or have a suggestion for improving our content, we would appreciate your feedback.  Just  e-mail:  

and include the URL for the page.


Burleson Consulting

The Oracle of Database Support

Oracle Performance Tuning

Remote DBA Services


Copyright © 1996 -  2017

All rights reserved by Burleson

Oracle ® is the registered trademark of Oracle Corporation.

Remote Emergency Support provided by Conversational