Data Modelling Essentials

Topics

• Data Model Components
  • How to identify Entities and Subtypes
  • Data Modelling Basics; Entities, Attributes, Relationships
  • How do different data modelling notations represent subtypes?
  • What are the differences between exclusive and non-exclusive subtypes?
  • Relationships: Cardinality & Optionality, Identifying, Non-identifying, recursive, and many-to-many
  • Basic standards that you can use right away
  • Rules for handling Super types, subtypes, many to many and recursive relationships
  • How does cardinality and referential integrity lead to better data quality?
  • What are the alleged and actual benefits of surrogate keys?
  • Keys: Primary, Natural, Surrogate, Alternate, Inverted, Foreign
  • Attribute properties & attribute domains
• Data Modelling Basics
  • What is the relationship between a data model and other types of models in the Enterprise Architecture
  • What is Data Modelling and why does it matter
  • The major differences between Enterprise, Conceptual, Logical, Physical and Dimensional data models
  • What is a Conceptual Data model, why it`s important and the pivotal role it plays in all architecture disciplines
  • Data vs MetaData; what`s the difference and why does it matter
• Using Data Models
  • The critical role played by Data Models in all disciplines of Information Management
  • How to use high-level data models to communicate with business people to get the core information you require to build robust applications
  • Data models are not just for DBMS design, the other areas where models are critical
  • Why Data Models are required for software package implementation
  • Maturity assessment to consider the way in which models are utilized in the enterprise and their integration in the System Development Life Cycle (SDLC)
• Creating Data Models
  • What core information is needed to create a data model, how this can be easily communicated to business people, and what visual constructs to use to get their attention
  • How to get started with data models
  • How to capture requirements for data models
  • Templates and guidelines for a step-by-step approach to implementing a high-level data model in your organization
  • Approaches for creating a data model (Top Down, Bottom Up, Middle out) and when to use them
• Improving your Data Models
  • Normalisation: 1st, 2nd and 3rd normal form and a brief overview of other normal forms
  • Data Modelling Notations and tooling
  • Layout, presenting, and communicating a data model to non-modellers
  • Ten steps for checking the quality of your data models
• Dimensional Data Modelling Basics
  • The key differences between Dimensional & Relational models
  • Facts and Dimensions, the basics of Dimensional models
  • Inmon vs Kimball Data Warehouse approaches
  • The use of Dimensional data models in Business Intelligence & Data Warehousing
  • Aggregation and Summarisation - what you really need to know
  • How to cater for change in Dimensional models; the different types of slowly changing dimensions
  • Columnar Database & Data warehouse - a forgotten treasure?

Who should Attend

• Data Architects
• Data Modellers
• Enterprise Architects
• Data Analysts
• Application Architects
• Solution Architects
• Business Analysts
• Information Architects
• Developers
• Database Administrators
• IT Consultants
• Project / Programme Managers
• Business Users