DATA MODELING ONLINE TRAINING

DATA MODELING COURSE CONTENT
I INTRODUCTION TO DATA MODELING
Data Modeling: An Overview
	Data Model Defined
	What Is a Data Model?
	Why Data Modeling?
	Who Performs Data Modeling?
	Conceptual Data Modeling
	Data Model Components
	Data Modeling Steps
	Data Model Quality
	Significance of Data Model Quality
	Data Model Characteristics
	Ensuring Data Model Quality
	Data System Development
	Data System Development Life Cycle
	Roles and Responsibilities
	Modeling the Information Requirements
	Applying Agile Modeling Principles
	Data Modeling Approaches and Trends
	Data Modeling Approaches
	Modeling for Data Warehouse
Methods, Techniques, and Symbols
	Data Modeling Approaches
	Semantic Modeling
	Relational Modeling
	Entity-Relationship Modeling
	Methods and Techniques
II DATA MODELING FUNDAMENTALS
Anatomy of a Data Model
	Data Model Composition
	Models at Different Levels
	Conceptual Model: Review Procedure
	Conceptual Model: Identifying Components
	Creation of Models
	Entity Types
	Specialization Generalization
	Relationships
	Attributes
	Identifiers
	Review of the Model Diagram
	Logical Model: Overview
	Model Components
	Transformation Steps
	Relational Model
	Physical Model: Overview
	Model Components
	Transformation Steps
Entities in Detail
	Entity Types or Object Sets
	Comprehensive Definition
	Identifying Entity Types
	Generalization and Specialization
	Why Generalize or Specialize?
	Supertypes and Subtypes
	Generalization Hierarchy
	Recursive Structures
	Conceptual and Physical
	Modeling Time Dimension
	Categorization
	Entity Validation Checklist
	Completeness
	Correctness
Attributes and Identifiers in Detail
	Attributes
	Properties or Characteristics
	Attributes as Data
	Attribute Values
	Names and Descriptions
	Attribute Domains
	Definition of a Domain
	Domain Information
	Attribute Values and Domains
	Value Set
	Range
	Type
	Null Values
	Types of Attributes
	Single-Valued and Multivalued Attributes
	Simple and Composite Attributes
	Attributes with Stored and Derived Values
	Identifiers or Keys
	Need for Identifiers
	Definitions of Keys
Relationships in Detail
	Relationships
	Associations
	Relationship: Two-Sided
	Relationship Sets
	Double Relationships
	Relationship Attributes
	Degree of Relationships
	Unary Relationship
	Binary Relationship
	Ternary Relationship
	Quaternary Relationship
	Structural Constraints
	Cardinality Constraint
	Participation Constraint
	Dependencies
	Entity Existence
	Relationship Types
	Identifying Relationship
	Nonidentifying Relationship
	Maximum and Minimum Cardinalities
	Mandatory Conditions: Both Ends
	Optional Condition: One End
	Optional Condition: Other End
	Optional Conditions: Both Ends
	Special Cases
	Gerund
	Aggregation
	Access Pathways
	Design Issues
	Relationship or Entity Type?
	Ternary Relationship or Aggregation?
	Binary or N-ary Relationship?
	One-to-One Relationships
	One-to-Many Relationships
	Circular Structures
	Redundant Relationships
	Multiple Relationships
	Relationship Validation Checklist
	Completeness
	Correctness
Data Normalization
	Informal Design
	Forming Relations from Requirements
	Potential Problems
	Update Anomaly
	Deletion Anomaly
	Addition Anomaly
	Normalization Methodology
	Strengths of the Method
	Application of the Method
	Normalization Steps
	Fundamental Normal Forms
	First Normal Form
	Second Normal Form
	Third Normal Form
	Boyce-Codd Normal Form
	Higher Normal Forms
	Fourth Normal Form
	Fifth Normal Form
	Domain-Key Normal Form
	Normalization Summary
	Review of the Steps
	Normalization as Verification
Modeling for Data warehouse
	Decision-Support Systems
	Need for Strategic Information
	History of Decision-Support Systems
	Operational Versus Informational Systems
	System Types and Modeling Methods
	Data Warehouse
	Data Warehouse Defined
	Major Components
	Data Warehousing Applications
	Modeling: Special Requirements
	Dimensional Modeling
	Dimensional Modeling Basics
	STAR Schema
	Snowflake Schema
	Families of STARS
	ransition to Logical Model
	OLAP Systems
	Features and Functions of OLAP
	Dimensional Analysis
	Hypercubes
	OLAP Implementation Approaches
	Data Modeling for OLAP
	Data Mining Systems
	Basic Concepts
	Data Mining Techniques
	Data Preparation and Modeling
	Data Preprocessing
	Data Modeling