Fundamentals of Data Modeling

Learn the fundamentals of Data Modeling and take your career to new heights.

(DATA-MODEL.AO1) / ISBN : 978-1-64459-301-1
This course includes
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TestPrep
Hands-On Labs
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About This Course

It is a comprehensive Data Modeling course that focuses on data-centric design principles, relational modeling components, and the process of creating conceptual, logical, and physical data models. You’ll learn how to create various data models using diagramming alternatives like flowcharts, data flow diagrams, and fishbone diagrams. Discover the components of a relational database model, including conceptual, logical, and physical models. By the end of this online Data Modeling training course, you’ll have the essential skills and expertise to design and implement effective data structures for various applications.

Skills You’ll Get

  • Knowledge of data-centric design principles
  • Create various data models: conceptual, logical, and physical
  • Expertise in using diagramming techniques
  • Knowledge of relational database models
  • Handling temporal data
  • Apply normalization techniques
  • Understanding of Unified Data Model (UNL) 
  • Understanding of enterprise data modeling

Interactive Lessons

13+ Interactive Lessons | 101+ Exercises | 178+ Quizzes | 107+ Flashcards | 107+ Glossary of terms

Gamified TestPrep

52+ Pre Assessment Questions | 52+ Post Assessment Questions |

Hands-On Labs

21+ LiveLab | 18+ Video tutorials | 00+ Minutes

1

Introduction

  • Who Should Read This Course
  • What the Course Covers
2

Introduction to Data Modeling

  • Data-Centric Design
  • Anatomy of a Data Model
  • Importance of Data Modeling
  • Measures of a Good Data Model
  • How Data Models Fit Into Application Development
  • Data Modeling Participants
3

Relational Model Components

  • Conceptual and Logical Model Components
  • Physical Model Components
4

Data and Process Modeling

  • Data Model Diagramming Alternatives
  • Process Models
  • Unified Modeling Language (UML)
  • Relating Entities and Processes
5

Organizing Database Project Work

  • The Traditional Life Cycle
  • Nontraditional Life Cycles
  • The Project Triangle
6

Conceptual Data Modeling

  • The Conceptual Modeling Process
  • Creating the Model
  • Evaluating the Model
7

Logical Database Design Using Normalization

  • The Need for Normalization
  • Applying the Normalization Process
  • Denormalization
  • Practice Problems
8

Beyond Third Normal Form

  • Advanced Normalization
  • Resolving Supertypes and Subtypes
  • Generalizing Attributes
  • Alternatives for Reference Data
9

Physical Database Design

  • The Physical Design Process
  • Designing Tables
  • Integrating Business Rules and Data Integrity
  • Adding Indexes for Performance
  • Designing Views
10

Alternatives for Incorporating Business Rules

  • The Anatomy of a Business Rule
  • Implementing Business Rules in Data Models
  • Limitations on Implementing Business Rules in Data Models
  • Functional Classification of Business Rules
11

Alternatives for Handling Temporal Data

  • Temporal Data Structures
  • Calendar Data Structures
  • Business Rules for Temporal Data
12

Modeling for Analytical Databases

  • Data Warehouses
  • Data Marts
  • Modeling Analytical Data Structures
  • Loading Data into Analytical Databases
13

Enterprise Data Modeling

  • Enterprise Data Management
  • The Enterprise Data Model

2

Introduction to Data Modeling

  • Creating a Conceptual Model
  • Creating a Physical Data Model
  • Creating a Logical Data Model
3

Relational Model Components

  • Modifying a Conceptual Model
4

Data and Process Modeling

  • Drawing of a Conceptual Model with Nested Subtypes
5

Organizing Database Project Work

  • Discussing the Traditional Life Cycle and Requirements Gathering
  • Testing the Knowledge of Project Database Management Tasks
  • Discussing Nontraditional Life Cycles and the Project Triangle
6

Conceptual Data Modeling

  • Creating a Conceptual Model for the Employee Management System
7

Logical Database Design Using Normalization

  • Creating a Data Model in Second Normal Form
  • Creating a Data Model in First Normal Form
  • Analyzing Normalization in Academic Tracking Database
8

Beyond Third Normal Form

  • Creating a Data Model in Fourth Normal Form
  • Creating a Complex Logical Data Model
9

Physical Database Design

  • Converting a Logical Data Model into a Physical Data Model
  • Creating a Physical Data Model ERD
  • Creating a Data Model in Third Normal Form
10

Alternatives for Incorporating Business Rules

  • Modeling Business Rules in a Logical Data Model
11

Alternatives for Handling Temporal Data

  • Adding History to Data Models
12

Modeling for Analytical Databases

  • Designing a Star Schema Fact Table
13

Enterprise Data Modeling

  • Developing an Enterprise Conceptual Model

Any questions?
Check out the FAQs

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It is an intermediary level course that focuses on design and implementation of effective data structure models for various applications.

This Data Modeling Certification course introduces you to an array of modeling techniques including:

  • Entity-Relationship (ER) Modeling
  • Data Flow Diagrams (DFDs)
  • Unified Modeling Language (UML)
  • Normalization & Denormalization Processes
  • Data Warehousing & Data Marts
  • Enterprise Data Modeling

Yes, you’ll be awarded a certificate of completion.

There’s plenty of interactive study material available with this course including hands-on Labs, video lessons, gamified test-prets, glossary, flashcards, quizzes, and pre and post assessments.

Yes, there are pre and post assessments included with the course.

No need to worry about your practice. This course is fully equipped with hands-on-Labs that enables you to practice your learning in a safe environment.

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