Clariteq Data Modeling Workshop

A Business-Oriented Approach to Entity-Relationship Modeling ~ 2 days

Description

Data modeling was originally developed as a tool for improving database design, but has become a fundamental analysis technique in modern application development, whether the analyst is primarily concerned with data structures, application logic, the user interface, or business processes.

A key driver is that applying data modeling early in requirements definition allows analysts and clients to develop a common understanding of the business entities (e.g., Customer, Order, Product, Part, etc.) that business processes and information systems deal with, their interrelationships, and the rules that govern them.  This eliminates the problems of inconsistent terminology and conflicting assumptions that otherwise plague application development.

This workshop introduces entity-relationship modeling from a non-technical perspective, thoroughly covering the basic components of a data model - entities, relationships, attributes, and identifiers.  In addition to showing how and when to use these components in developing a data model, it includes many tips, quality checklists, and common pitfalls.  Just as important, it contains far more advice on the process of developing a data model than other courses, including specific methods for getting subject matter experts involved and maintaining their commitment.

 

Objectives:

On workshop completion, participants will be able to:

  • Use entity-relationship modeling to depict facts and rules about business entities at different levels of detail, including conceptual (overview) and logical (detailed) models
  • Use top-down and bottom-up approaches to initiating development of a data model
  • Recognize the four basic patterns in data modeling, and when to use them
  • Effectively use definitions and assertions (“rules”) as part of data modeling
  • Use an intuitive approach to data normalization within an entity-relationship model
  • Apply various techniques for discovering and meeting additional requirements
  • Read a data model, and communicate with specialists using the appropriate terminology

Prerequisites:

An understanding of information systems concepts.

Target Audience:

Business analysts and application developers responsible for the analysis and design of any component of an application, including the database, application logic, or the user interface.  Also, business professionals and managers needing to understand how this technique can uncover and resolve inconsistency in business terminology, policy, and rules.

Course Outline / Topics:

  • Overview of data modeling: terminology, types of models, and key concepts
  • The essential data model components - entities, relationships, attributes, and identifiers
  • A three-phase approach to completing a data model
  • Initiating a conceptual data model using a bottom-up approach
  • Four common errors in identifying entities, and how to avoid them
  • Eliminating confusion and misunderstanding with well-structured entity definitions
  • Four entity types, and rules and guidelines for dealing with them
  • Adding detail and rigor - evolving the conceptual model into a logical data model
  • Patterns for common situations - multi-valued attributes, redundant data, and reference data
  • The world's simplest guide to normalization
  • Primary and foreign keys in logical data models
  • Meaningless primary keys – rationale and limitations
  • Specifying assertions and constraints – rules that can’t be shown on the E-R diagram
  • Drawing the Entity-Relationship Diagram for maximum readability
  • Techniques for discovering, assessing, and meeting new requirements
  • Wrap-up – summaries and resources

 

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