(DATA-MODEL.AO1) / ISBN : 978-1-64459-301-1
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Lessons
TestPrep
Hands-On Labs
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Lessons

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

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

1

Introduction to Data Modeling

  • Creating a Conceptual Model
  • Creating a Physical Data Model
  • Creating a Logical Data Model
2

Relational Model Components

  • Modifying a Conceptual Model
3

Data and Process Modeling

  • Drawing of a Conceptual Model with Nested Subtypes
4

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
5

Conceptual Data Modeling

  • Creating a Conceptual Model for the Employee Management System
6

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
7

Beyond Third Normal Form

  • Creating a Data Model in Fourth Normal Form
  • Creating a Complex Logical Data Model
8

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
9

Alternatives for Incorporating Business Rules

  • Modeling Business Rules in a Logical Data Model
10

Alternatives for Handling Temporal Data

  • Adding History to Data Models
11

Modeling for Analytical Databases

  • Designing a Star Schema Fact Table
12

Enterprise Data Modeling

  • Developing an Enterprise Conceptual Model

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