Data modeling provides a vehicle for users and information professionals throughout the organization to work together to clearly and consistently articulate business rules and requirements. Building data models allows an organization to identify the important data needed for business purposes, without regard to a specific application or implementation. Application data models should follow an integrated approach to information architecture and data model development that leads to stable, flexible and reusable database designs, and to the eventual creation of an enterprise data model.

This course is designed to teach students how to model the data needed by the enterprise and for applications. This three-day interactive course provides a combination of lecture and small workshop exercises using a continuing case study that allows the student to grasp and practice the concepts of data modeling. It blends basic data modeling activities and concepts with the enterprise view of business data needs. It can be presented using a particular modeling tool or can be taught independent of any modeling tool.

This EWSolutions-certified course is workshop-focused since design concepts are best learned from doing. The workshops are oriented to solving problems that you have in your current projects. The workshops allow you to learn how the concepts are applied and how to develop skills in data modeling from conceptual, to logical to physical.

Objectives

The objectives of the course are to:

• Analyze an enterprise or business area, identifying data components and relationships among them
• Describe how to analyze the correct relationships between entities
• Determine how to actively engage business people in data modeling
• Model data for an application or for the enterprise and represent it via entity-relationship diagrams
• Validate the model using normalization
• Understand design compromises among flexibility, performance, ease of use and cost
• Understand considerations for the physical database design

Seminar Content

• Roles, Definitions and Key Principles
  • Critical role of the business analyst / data analyst in the enterprise
  • Creating and adopting a formal modeling strategy across the enterprise
  • Roles and mutual expectations among team members of a data modeling project
• Capturing Requirements for a Data Model
  • Identify critical consumers
  • Understand the structure of a data model
  • The data development life cycle as a business value chain
  • Business resource approach to data modeling
  • Deriving a detailed data model within an architecture framework
  • Fundamental, associative and attributive entity types
  • Data definition quality
• Requirements
  • Attributes and types of enterprise requirements versus application requirements
  • Discovering the meaning of data
  • Discovering and modeling business rules
  • Verifying the placement of data within the model
  • Requirements elicitation techniques
    1. The various types of requirements gathering techniques
    2. Advantages and disadvantages of the techniques in data modeling

Data Modeling Concepts and Principles

• Phases of application development
• Importance of building data models
• Overview of the types of data models
• Entities, attributes and relationships
• Static and dynamic entity types
• Identifier, descriptive and relationship attribute types
• Discovering the meaning of data
• Discovering and modeling business rules
• Verifying the placement of data within the model
• Information architecture quality

The Data Modeling Process

• Relationship types
• E-R diagrams and how to read them
• Keys in enterprise data modeling
• Normalization for the enterprise
• Patterns in data modeling
• Addressing missing data and data redundancy
• Sub-Entity modeling
• Identifier integrity
• Recursive relationships
• Modeling entity types and subtypes
• Generic (metadata) entity types

Logical to Physical Data Modeling

• A logical database design
• Relational database terms
• Views
• Indexes
• Constraints
• Sequences
• Triggers
• Rules for constructing a relational schema
• The physical model: internal organization of data and access methods
• Uses of a physical model

Special Topics in Data Modeling

• Model meta data
• Supporting multiple business views
• Data model walkthroughs
• Reconciling the data model
• Techniques for effective workshops
• Gaining and sustaining management commitment and involvement

Conclusion

• Workshop Summary, Additional Exercises and Reference Materials
• Copies of the book “Data Modeling Made Simple” by Steve Hoberman