Course Code: dmbk5
Duration: 21 hours
Prerequisites:
  • CDMP Fundamentals
Overview:

Course Description

The course covers Data Warehousing and Business Intelligence within the DAMA Body of Knowledge (DMBoK®) in depth. What is data warehousing and Business Intelligence (BI) Management? Why are they important Data Management disciplines? What types of models are there? This course covers these questions, along with various characteristics of data warehouse and BI platforms, dimensions and hierarchies, dimensional modeling, E/R modeling, implementation of warehouses and marts, data visualization, and more. It also addresses the fundamentals of Big Data.

Purpose

To learn about the many different elements of data warehousing and BI.

Outcome

  • Understand why and how data warehousing is used
  • Learn about primary data warehousing architectures
  • Explore dimensional modeling, types of BI, analytics, and visualizations
Course Outline:
  • Overview
    • CDMP Breakdown
    • Recognizing Data Warehousing and Business Intelligence Management within the DAMA DMBoK Wheel
    • Drivers and Goals of Data Warehousing and Business Intelligence
    • Why Use a Data Warehouse?
    • Simplified Business Intelligence Stack
    • Conceptual DW/BI and Big Data Architecture
    • Big Data Definitions
    • Abate Information Triangle
    • Internet of Things Framework
  • Characteristics
    • What is Data Warehousing? (DMBoK)
    • What is Business Intelligence? (DMBoK)
    • Objectives of Business Intelligence
    • The Classic Characteristics of a Data Warehouse
  • DW Models
    • The Inmon Data Warehouse Model
    • The Corporate Information Factory
    • Classic Characteristics of a Data Warehouse
    • The Kimball Model
  • Tables and Dimensions
    • Dimension Hierarchies and Fact Tables
    • How do Dimensional Models Fit into the Data Warehouse?
    • Understanding Slowly Changing Dimensions
    • Why Do Slowly Changing Dimensions Present Problems?
    • Handling Methods of Slowly Changing Dimensions
    • Dimensional Model Design
    • Designing a Dimensional Model Using an E/R Model
    • Identifying Facts, Dimensions and Hierarchies
    • Design the Dimensional Model
    • The Need for Aggregate Tables
    • Tables Compared (Fact and Dimension)
    • Which Aggregates Should We Build?
  • DW and BI Activities
    • DW-BI Activities (DAMA)
    • Understanding Business Intelligence Information Needs
    • Defining and Maintaining the DW-BI Architecture
    • Implementing Data Warehouses and Data Marts
    • Implementing Business Intelligence Tools and User interfaces
  • Data Visualization
    • What is Data Visualization?
    • Visualization Types
    • Processing Data for Business Intelligence
    • Monitoring and Tuning the Data Warehousing Process
    • Monitoring and Tuning BI Activity and Performance
    • KPI’s Hierarchy
  • Tools and DBMS
    • Types of Business Intelligence Tools
    • Columnar DBMS
  • Wrap Up
    • Key Takeaways