Data Warehousing Fundamentals

What you will learn:
In this course, students study the issues involved in planning, designing, building, populating, and maintaining a successful data warehouse. Students learn the reasons why data warehousing is a compelling decision-support solution in today's business climate. Participants also examine what Oracle has to offer to a successful data warehouse implementation by identifying the proven Data Warehouse and Business Intelligence (DW and BI) technologies and tools provided by Oracle. However, since this course covers the fundamentals, the DW and BI tools are introduced, as it is not possible to cover each of these tools extensively in this two-day course. So the practices are mainly scenario driven.

Students who can get benefit from this course:
Data Warehouse Administrator
Database Administrators
Project Manager

Prerequisites:
Introduction to Oracle9i: SQL
Oracle 9i Database Fundamentals I

Course Objectives:
Describe methods and tools for accessing and analyzing warehouse data
Define the decision-support purpose and end goal of a data warehouse
Explain the implementation and organizational issues surrounding a data warehouse project
Describe the various technologies required to implement a data warehouse

Course Topics:

Business Intelligence and Data Warehousing
The road map to Business Intelligence (BI)
Data warehouses compared with Online Transaction Processing (OLTP)
Management information systems and decision support systems (DSS)
Business drivers for data warehouses
Typical uses of a data warehouse

Defining Data Warehouse Concepts and Terminology
Common data warehouse definitions
Data warehouse properties and characteristics
Warehouse development approaches
Components of data warehouse design and implementation
Components of a data warehouse
Data warehouse compared with data mart
Dependent and independent data marts

Planning and Managing the Data Warehouse Project
Managing financial issues
Obtaining business commitment
Gathering business and user requirements
Evaluating the warehouse project
Implementation processes and requirements

Modeling the Data Warehouse
Data warehouse database design phases
Defining the business model
Choosing the architecture
Creating the dimensional model
Using time in the data warehouse
Using summary data
Query rewrite
Creating the physical model

Building the Warehouse - Extracting Data
Extracting, transforming, and loading data
Examining data sources
Extracting data
Extraction techniques

Building the Data Warehouse - Transforming Data
Transformation
Transforming data: problems and solutions
Resolving quality data issues
Transformation techniques
Transformation tools

Building the Data Warehouse - Loading Warehouse Data
Loading data into the warehouse
Building the loading process
Loading the data
Post-processing of loaded data
Verifying data integrity

Refreshing Warehouse Data
Capturing and applying changed data
Batch load requirements
Limitations of methods in applying change
Purging and archiving data
Leaving a Metadata Trail
Defining warehouse metadata
Developing a metadata strategy
Examining types of metadata
Metadata management tools
Common warehouse metadata

Managing the Data Warehouse
Managing the transition to production
Managing growth
Managing backup and recovery
Identifying data warehouse performance issues

On Every Module Student gets :

JAVA
Introductory Offer