Course Code: dmbk6
Duration: 21 hours
Prerequisites:
  • CDMP Fundamentals
Overview:

The course covers Data Modeling within the DAMA Body of Knowledge (DMBoK®) in depth. It explores numerous essential features of contemporary Data Modeling, including the System Development Lifecycle (SDLC), modeling styles, analysis and solution design, detailed data designs, Design Quality Management, types of data models, and data implementation, among many others.

Purpose

To gain an in-depth understanding of Data Modeling, data design, and its key components.

Outcome

  • Understand the physical implementation of data models
  • Learn about data development in the context of system development and maintenance activities
  • Explore how to focus on providing data models and designs for business applications and solutions
  • Discuss many different data model styles and implementations
Course Outline:
  • Data Modeling and the DMBoK
    • Data Modeling and Database Design within the DMBoK Wheel
    • CDMP Breakdown
    • Defining Data Modelling and Design
  • Data Modeling – Overview, Key Points, and the SDLC
    • Understanding Data Development
    • Information Lifecycle and SDLC
  • Data Modeling – Data Models
    • What is a Data Model?
    • Data Model Representations
    • The Importance of Data Modelling
    • Top Reasons for Producing a Data Model
    • Levels of Data Model
    • Entity Relationship Symbols (Information Engineering)
    • Cardinality and Notations
    • Enterprise Data Model
    • Subject Area Model (aka Enterprise)
    • The Conceptual Data Model
    • Logical Data Models
    • Physical Data Model
    • Enterprise vs. Conceptual vs. Logical
  • Data Modeling – Entities
    • Data Model Representations
    • Dependent and Independent Entities
    • The Importance of Understanding Entities
  • Data Modeling – Attributes
    • Attribute Properties and Domains
    • Creating a Domain
    • Domain Inheritance
  • Data Modeling – Relationships
    • Relationship Types
    • The Concept of Many-to-Many Relationships
    • Resolving a Many-to-Many Relationship
    • Recursive Relationships
    • Role Name Usage with Relationships
    • Entity Subtypes
  • Data Modeling – Keys
    • Terms Used Conceptually and Physically
    • Entity Keys
    • Primary Key Criteria
    • Alternate Keys
    • Pros and Cons of Surrogate Keys vs. Natural Keys
    • The Process and Data Model Relationship
    • Logical Data Model Components
  • Data Modeling – Normalization
    • Defining Normalization
    • Normalization Approaches
    • Normalization Rules
  • Data Modeling – Database Design
    • Database Design Principles (PRISM)
    • Physical Database Design Best-Practice
    • Transforming Logical to Physical Data Model
    • Understanding Partitioning
    • Classification Types of Various Data Modelling Tools
    • ACID Test for Transaction Processing
    • BASE: The Alternative to ACID
  • Wrap Up
    • Key Takeaways