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 Modeling 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 modeling 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 organizational 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 organization.  

1. Data Flow Diagrams (DFDs) and Functional Decomposition Diagrams (FDDs)

a. Developing DFDs and FDDs
b. Identifying the business area
c. Modeling essential business processes (FDDs)
d. Documenting data use in business processes (DFDs)
e. Understanding their relationship to logical data models

2. Identifying and Describing the Conceptual Data Model

a. Naming entities, attributes and relationships
b. Discovering and defining entities
c. Analyzing attributes
d. Defining cardinality in relationships
e. Understanding concatenated and surrogate unique identifiers

3. The Logical Data Model

a. Developing the detailed logical data model
b. Identifying and applying entity types
c. Modeling with subtypes and supertypes
d. Understanding attributive and associative entities
e. Understanding multivalued attributes
f. Documenting the logical data model
g. Analyzing data using the CRUD matrix

4. Context-Level Data Flow Diagrams

a.Developing diagrams that represent processes, external agents and data flows
b. Defining and naming diagram components
c. Drawing divergent and convergent data flows
d. Leveling the data flow diagram
e. Avoiding common errors in diagramming

5. The Transition to OO/UML

a. Understanding the Unified Modeling Language (UML)
b. Applying use case, class state and activity diagrams

6. Other Key Topics

a. Applying normalization rules
b. Understanding the physical data model
c. Describing the functions and benefits of CASE tools
d. Verifying and presenting models to increase project success