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DM 101 – Data Modeling for Managers and Executives

Duration: 1 - 2 days

This course is designed to teach managers and executives about the process of logical data modeling and demonstrate the methods their analysts will use to model the data needed by a project or the enterprise.

data virtual screen and business man using touchs 2023 11 27 04 58 34 utc

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Description

This course is designed to teach managers and executives about the process of logical data modeling and demonstrate the methods their analysts will use to model the data needed by a project or the enterprise. This 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 logical data modeling. It blends basic data modeling activities and concepts with the enterprise view of business data needs.

Objectives

  • Demonstrate to managers and executives the concepts and processes used in logical data modeling
  • Explain how analyst approach an enterprise or business area, identifying data components and relationships among them
  • Show how analysts model data for an enterprise and represent it via entityrelationship diagrams
  • 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 enterprise modeling strategy
    • Roles and mutual expectations among team members of an enterprise data modeling project
  • Capturing Requirements for Data Modeling
    • Identify critical consumers
    • Understand the structure of a Data Model
  • Types of Requirements
    • Attributes and types of enterprise requirements versus application requirements
  • Review of Data Modeling Concepts and Principles
    • Phases of application development
    • Importance of building data models
    • Overview of the types of data models
  • The Data Modeling Process – An Overview
    • 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
    • Issues and Challenges for Data Modeling and Data Analysis
  • Conclusion
    • Workshop Summary, Additional Exercises and Reference Materials

About the Course Designer

This training was designed by David Marco, PhD, an internationally recognized authority on data and AI governance, to help teams succeed in real organizational conditions. The curriculum equips participants with practical judgment, shared language, and decision clarity that hold under scale, risk, and executive accountability.

David Marco PHD EWSolutions

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