What you will learn
After completing this course, the student should be able to:
  • Understand and apply the concepts, processes and principles of data warehousing
  • Identify the components of a data warehouse architecture
  • Be familiar with data warehouse terminology
  • Identify success and risk factors of data warehousing
  • Place deliverables within the context of a comprehensive data warehousing process
  • Take practical steps to begin a success data warehousing initiative
Audience
  • Anyone new to data warehousing
  • Those who want to review the fundamentals of data warehousing from a best practices standpoint
  • Business and systems managers who are evaluating data warehousing
Prerequisites

There are no prerequisites

Duration
2 days

Outline for Introduction to Data Warehousing Training

1. Introduction to Data Warehousing

  • Basic Concepts and Definitions
    • Definition of the data warehouse (DW)
    • Overall architecture of a DW
    • DW processes
    • Categories of DW technology
    • DW project and initiative types
  • Project Management Deliverables
    • DW strategy
    • DW project scope
    • DW project plan
    • Managing a DW project
    • The iterative release model
  • Introduction to the Dimensional Model
    • Facts
    • Dimensions
    • Star schemas
    • Snowflakes
  • Architectural deliverables
    • Requirements
    • Analysis
    • Design
    • Infrastructure
    • Implementation

2. Implementation, Operation and Expansion

  • Implementation Deliverables
    • Outcomes from analysis
    • Outcomes from design
    • Outcomes from construction
    • Outcomes from deployment
    • Operational Deliverables
    • Service level agreements
    • Outcomes of usage
    • DW monitoring
    • DW governance
  • Maintaining the DW
    • Incremental DW releases
    • Follow-up to DW
    • On-going assessment
    • Post mortem and lessons learned
    • Managing consultants
    • Managing the vendor
    • Getting started with data warehousing