Logical Data Modelling Communicate business and project requirements to project stakeholders using conceptual and logical data models Course information Duration: 3 days PDUs: 22.5 Course Fee: £1495 excl. VAT €1795 excl. VAT Related links     Ask a question about this course     Download description Take a Pre- and Post-course assessment Select a Public Classroom Course Aligning Project Management with Organisational Strategy Business Process Analysis, Innovation and Design Coaching and Mentoring for Improved Performance Contract Management Principles and Practices Critical Thinking and Problem Solving Establishing the Project Management Office Facilitation Techniques for Requirements Development Financial Management for Project and Contract Managers Foundations of Business Analysis How to Gather and Document User Requirements Introduction to Business Analysis Leading Complex Projects Leading Project Managers Logical Data Modelling Managing Global Projects Managing Information Technology Projects Managing Projects Negotiation Skills PgMP® Exam Preparation PMP® Exam Preparation PMP® Power Exam Preparation Process Modelling Management Programme Management Project Leadership, Management and Communications Quality for Project Managers Rapid Assessment and Recovery of Troubled Projects Requirements Management: A Key to Project Success Risk Management Scheduling and Cost Control Simulation: Project Management Applications Systems Integration Project Management Taking Charge of Organisational Change Testing Techniques for Tracing and Validating Requirements Use Case Modelling Writing Statements of Work: The Heart of Any Contract     Register for a course by clicking a date below Central London 27-29 Apr 09 26-28 Oct 09

You will learn how to:

• Create logical data models to define business and project requirements
• Explain the purpose, importance, and uses of logical data modeling in the requirements gathering process
• Describe the elements of data flow diagrams and functional decomposition diagrams and their relationship to logical data models
• Explain a logical data model to stakeholders
• Apply logical data modelling to the overall software development life cycle and respond to business management issues

Course Synopsis

The ability to communicate business processes and information needs is central to the success of any software development project. Explaining user needs is a major challenge as well as an opportunity. The business analyst who understands structured modelling has a distinct advantage in addressing and communicating requirements. The use of models can greatly increase all stakeholders’ understanding of a project’s business rules and data management requirements.

Logical Data Modelling explores business rules, policies and procedures and how they can be modelled effectively. Participants will learn entity relationship diagramming, super and sub-types, attributive and associative entities, and documenting data constraints. You will also learn how to create models without being limited by technology or organisational structure.

You will leave this course ready to communicate business and project requirements to project stakeholders using conceptual and logical data models. In short, you will be able to integrate multiple business units so that you understand the big picture of your organisation.

Course Topics

1. Data Flow Diagrams (DFDs) and Functional Decomposition Diagrams (FDDs)
   1. Developing DFDs and FDDs
   2. Identifying the business area
   3. Modelling essential business processes (FDDs)
   4. Documenting data use in business processes (DFDs)
   5. Understanding their relationship to logical data models
2. Identifying and Describing the Conceptual Data Model
   1. Naming entities, attributes and relationships
   2. Discovering and defining entities
   3. Analysing attributes
   4. Defining cardinality in relationships
   5. Understanding concatenated and surrogate unique identifiers
3. The Logical Data Model
   1. Developing the detailed logical data model
   2. Identifying and applying entity types
   3. Modelling with subtypes and supertypes
   4. Understanding attributive and associative entities
   5. Understanding multivalued attributes
   6. Documenting the logical data model
   7. Analysing data using the CRUD matrix
4. Context-Level Data Flow Diagrams
   1. Developing diagrams that represent processes, external agents and data flows
   2. Defining and naming diagram components
   3. Drawing divergent and convergent data flows
   4. Levelling the data flow diagram
   5. Avoiding common errors in diagramming
5. The Transition to OO/UML
   1. Understanding the Unified Modeling Language (UML)
   2. Applying use case, class state and activity diagrams
6. Other Key Topics
   1. Applying normalisation rules
   2. Understanding the physical data model
   3. Describing the functions and benefits of CASE tools
   4. Verifying and presenting models to increase project success

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