Data Warehousing Fundamentals

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Course Overview

In this course, students study the issues involved in planning, designing, building, populating, and maintaining a successful data warehouse.

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

Audience

• Database Administrators
• Implementation Team
• Project Manager
• Data Warehouse Designer
• Data Warehouse Administrator

Skills Gained

Students learn the reasons why data warehousing is a compelling decision-support solution in today's business climate. During the course, students examine Oracle warehouse technology, and identify the technology available from Oracle Partners for designing, implementing, and running a data warehouse.

Prerequisites

• Introduction to Oracle9i: SQL

Course Outline

Lesson One: 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

Lesson Two: 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

Lesson Three: 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

Lesson Four: 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

Lesson Five: Building the Warehouse - Extracting Data

• Extracting, transforming, and loading data
• Examining data sources
• Extracting data
• Extraction techniques

Lesson Six: Building the Data Warehouse - Transforming Data

• Transformation
• Transforming data: problems and solutions
• Resolving quality data issues
• Transformation techniques
• Transformation tools

Lesson Seven: 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

Lesson Eight: Refreshing Warehouse Data

• Capturing and applying changed data
• Batch load requirements
• Limitations of methods in applying change
• Purging and archiving data

Lesson Nine: Leaving a Metadata Trail

• Defining warehouse metadata
• Developing a metadata strategy
• Examining types of metadata
• Metadata management tools
• Common warehouse metadata

Lesson Ten: Managing the Data Warehouse

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

Follow On Courses

• Oracle9i Database: Program with OLAP DML

Data Warehousing Fundamentals / D16310GC10