THE DATA WAREHOUSE DEVELOPMENT METHODOLOGY

BACKGROUND: The data warehouse enables users to access vast stores of integrated, operational data to track business trends, facilitate forecasting and planning efforts, and make strategic decisions. It is not a single product, but rather a flexible environment comprised of multiple technologies. The software life cycle development process used for operational projects does not apply since the requirements are often unknown up front until the completion of the first pilot. This course focuses on DM&A’s proven methodology.

The core of this course is directed toward understanding deliverables that may be produced throughout the data warehousing development process.

DESCRIPTION: This seminar is a combination lecture and workshop, wherein the attendee will learn the process of identifying business requirements, documenting those requirements, building the project plan, managing the scope, using data models, etc. to deploy complete enterprise or data mart centric solutions.

Upon completing this seminar the student will be able to:

• Conduct a Readiness Assessment
• Gather Requirements
• Determine a pilot projects scope
• Create the project Plan
• Understand all of the team members tasks and
• Be able to manage the Data Warehouse Project using DM&A’s
• Attendees will also receive discounts toward "Building A Better Data Warehouse" book and the "Data Warehouse Development Methodology " CD-ROM Toolkit which contains templates and examples of all the key deliverables in managing a data warehouse project.

WHO SHOULD ATTEND: Data warehouse project managers, system developers, system and data architects, database administrators, and those interested in how data can be turned into information and how to compete in the marketplace with information.

INSTRUCTOR: Don Meyer is president of Data Mining & Analysis, LLC. He advises clients on all aspects of database administration, Unix/network administration, client/server and data warehouse implementations, including conducting training courses and, conducting database performance audits. Don is Oracle 7 DBA Certified and has published articles on client/server downsizing migrations.

SEMINAR OUTLINE

Introduction to Data Warehouse

• Definitions of common terms
• OLTP –vs- OLAP
• Introduction to key activities of methodology

Startup Phase

• Discussion of key roles involved
• Readiness assessment – and self-check test
• Techniques to address readiness shortfalls
• Critical Success Factors
• The pilot Project
• Assembling the Initial Team

Analysis Phase

• Determining Initial Business requirements
• Reviewing existing reports
• Organizing project Plan
• Identifying Project Scope
• Assembling Construction/Support Team
• Picking your tools overview

Design Phase

• Source System Analysis
• Building the three Data Models
• High Level Subject Area Conceptual Model
• Logical Model
• Enterprise and Subject Area Physical Models

• Capacity Planning and Sizing
• Designing Architecture
• Designing extraction/load processes
• Designing post load summary processes
• Designing metadata repository
• Designing Reports

Construction Phase

• Building DBMS
• Building Extraction, Transformation, and Load programs
• Building Post Load Data Mart Dimensions
• Building Post Load Data Mart Fact Tables
• Building Reports
• Building metadata
• Documenting process
• Utilizing Change Control Process

Testing Phase

• Data Quality Validation
• User Acceptance Testing
• Regression/System Load Testing

Implementation & Rollout

• Training Users on end user tool and their data
• Post review process

Workshop