Logical Data Modelling Course information Duration: 3 days PDUs: 22.5 Course Fee: £1395 excl. VAT €1875 excl. VAT Related links     Ask a question about this course     Download description   Register for a course 30 Jun-2 Jul 08 27-29 Oct 08

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 Financial Management for Project and Contract Managers How to Gather and Document User Requirements Introduction to Business Analysis Introduction to Testing for Business Analysts IT Risk Management Leading Complex Projects Leading Project Managers Logical Data Modelling Managing Global Projects Managing Information Technology Projects Managing Projects Negotiation Skills PMP® Exam Preparation PMP® Power Exam Preparation Process Modelling Management Programme Management Project Leadership, Management and Communications Project Management Applications Quality for Project Managers Rapid Assessment and Recovery of Troubled Projects Requirements Management: A Key to Project Success Risk Management Scheduling and Cost Control Systems Integration Project Management Taking Charge of Organisational Change Unlocking the Power of Earned Value Management Use Case Modelling for Business Analysis Writing Statements of Work: The Heart of Any Contract

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 the intersection of business processes and information/data needs is key to the success of any software development project. Understanding and explaining user needs is a major challenge and opportunity for the business analyst. The business analyst who understands structured modeling has a distinct advantage in addressing and communicating requirements. And the use of models can greatly increase all stakeholders’ understanding of the relevancy of business rules and data management requirements to the project at hand.

Logical Data Modelling explores business rules, policies and procedures and how they can be modeled effectively. Participants will learn entity relationship diagramming, super and sub-types, attributive and associative entities, and documenting data constraints. The logical data modelling approaches focus on the important requirements of the business that are discovered through significant user involvement during the analysis phase. You will also learn how to create models without being limited by technology or organisational structure.

You'll leave this course ready to communicate business and project requirements to project stakeholders using conceptual and logical data models. In short, you’ll 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. Modeling 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. Modeling with subtypes and supertype
   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. Leveling 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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