COURSE SYNOPSIS

This course presents how to analyze and create various models that define the static information content of a system.

These models include Business Rules, Entity-Relationship Diagrams, Class Models (Attributes and Operations), CRUD Matrixes, Data Dictionaries, Data Transformation and Mapping, and Metadata. Each of these techniques will be examined with hands-on exercises to create and review them.

Business analysts must address information and data needs when documenting business user requirements and analyzing work or process flows. Data modeling can be an intimidating challenge. However, understanding data usage is an essential component in solving business problems and the business analyst must be able to collect, organize, document, and present the end user’s data needs for a project to be successful.

In many organizations, the business analyst must work side-by-side with a data analyst or data modeler. This course presents the key concepts and techniques that a business analyst needs to understand to work effectively in this environment. The business analyst will learn the essential terminology and concepts of data to work in the relational data base environment whether it is on a mainframe or a web server.

Through lecture and hands-on workshops, this course presents how to define data entities, document their dependencies and relationships with other entities, and specify their attributes. The end result is an Entity Relationship Diagram that can be reconciled with process or use case models, and is easily understood by database specialists.

BABOK REFERENCE

This course addresses and expands Section 5.12.

COURSE OUTLINE

• Explain the data life cycle and how it relates to application development practices
• Explain the difference between conceptual, logical, and physical data modeling
• Identify data entities from process models and use cases
• Document relationships between entities and reconcile this to process models
• Create rough drafts of Entity Relationship Models (ERDs)
• Specify entity attributes and work with entity sub-types
• Create matrices for reconciling data and process models
• Discuss data normalization including 1st, 2nd, and 3rd normal forms
• Discuss the transition from logical data design to physical database definition

TOPICS

• Included in the seminar are the following key topics. Many more topics are covered, for more information download the course brochure.

  • Introduction to Data Modeling
  • Identifying Entities
  • Identifying and Documenting Entity Attributes
  • Defining Entity Relationships
  • Validating the Entity Relationship Diagram (ERD)
  • Understanding Entity Sub-Types
  • Normalization Practices

OUTCOMES

The student will understand the differences between various information/data models, and how to determine which may be best for a project. Additionally, hands-on experience will be gained with each technique.

This course does not address the use of automated tools.

LOGISTICS

• Class duration is days with workshops
• Instructional materials are provided
• This course is also offered as in-house training and may be combined with other courses.

PREREQUISITES

• None

AUDIENCE

• Information Technology Management
• Software Development Project Managers
• Product Managers and Product Implementation Teams
• End User Project Managers
• Business Analysts
• Information Technology Managers & Supervisors
• System Developers and Project Team Members
• Consultants and Project Auditors