Logical Data Modeling

Capture the flow of Business Data Logic.


Duration: 2 Days
Credits: 16 PDUs

Some experience in requirements elicitation and basic logical modeling.
Course Level

Intermediate to Advanced
Course Overview
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 taught in this engagement are designed to focus the attention on the important requirements of the business that are discovered through significant user involvement during the analysis phase. Participants will also learn how to create models without being limited by technology or organizational structure. It also provides an understanding of how the data elements are constructed, allowing for an integrated and seamless transition between the work of the BA and the data architect. 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. This engagement is replete with case studies and scenario and even a role play to aid absolute understanding and help with the retention of subject as well as help you understand complex elements with ease. 
Who should attend?
  • Analysts and information gatherers who need an efficient way of modeling the interfaces/processes that involve users and systems
  • Business analysts who need to define the business problem, business solution
  • Team leaders and systems architects
  • Database designers 
  • Software developers 
Performance Focus
  • Conceptual data and logical data
  • Entity relationships
  • Data normalization
  • Ability to effectively architect physical databases
  • Representation of “User” perception / representation of expected experience with business data
What You Will Learn
  • Describe how a lack of data governance can affect the risk exposure, cost control and profitability of your company.
  • Explain the role of the business analyst in gathering data-related requirements from stakeholders
  • Create, communicate and validate conceptual data models with your business stakeholders 
  • Create normalized logical data models as a hand-off to solution delivery 
Training Content and Basic Outline of the course

The Importance of Sound Data

  • Data is an organizational asset
  • The value of data to the organization
  • Big data

Conceptual Data Models

  • System development challenges
  • Data requirements
  • Models and modeling
  • Data, information and knowledge

Data Relationships

  • Naming standards for relationships
  • Relationship cardinalities
  • Relationships affected by time
  • Modeling time-dependent data
  • The importance of definitions
  • Alternative notations

Logical Data Models

  • Entity types
  • Subtyping
  • Attributive entities and multivalued attributes
  • Nondependence

Applying Logical Data Models

  • Associative entities
  • Data constraints
  • Using logical data models
  • Analysis of organizational and geographic data distribution
  • Supporting organizational data standards
  • Software acquisition

Data Normalization

  • Normalization and forms
  • The physical data model
  • Reverse engineering
  • The database designer
  • Denormalization

Verifying and Validating Data Models

  • Internal verification—ERD
  • Presenting data diagrams
  • Dos and don’ts of presenting data diagrams

Engagement End Recap and Vote of Thanks