Data Modeling Online Training | Data Modeling Training | Data Modeling Course

Data Modeling Course Content :
                               
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
•  Transition 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