Mastering Data Modelling Techniques

Topics

• Level Set Understanding & Terminology
  • Areas where Data modelling adds value to Data Management activities beyond Relational Database design
  • The need for and application of Data Models in Big Data and NoSQL environments
  • The critical role of Data models in other Data Management disciplines particularly Data Management and Data Governance
• Practical Application
  • How to discover requirements for robust data models
  • Conceptual and logical data models, and compromises for physical design
  • Where industry data models can provide a kick start
  • Where abstraction is valuable (and where it is risky)
  • How (and where) to apply standard solutions to well-known data modelling business scenarios
• Pragmatic Learning
  • How to create data models that can be easily read by humans
  • The best practices for developing Data models for Big Data and NoSQL environment
  • How to apply different Data modelling techniques
  • The difference between Enterprise, Conceptual, Logical, Physical and Dimensional Data models

Who should Attend

• Business Intelligence & Data Warehouse Developers & Architects
• Data Modellers
• Data Analysts
• Data Architects
• Solution Architects
• Enterprise Architects
• Information Architects
• Application Architects
• Developers
• Business Analysts
• Project / Programme Managers
• Database Administrators
• Data Governance Managers
• IT Consultants
• Information Quality Practitioners
• Data Quality Managers

Prerequisite: Attendance at the Data Modelling Essentials class OR 3+ years of practical Data Modelling experience.