Data modeling training

Hello sir I want to know the course outline of Data modeling training of Global Knowledge so please provide me information about the same.

[Shaleen]

A step by step guide to data modeling concepts and best practices underpinning sound database design

Course Outline

1. Introduction to Logical Data Modeling

Importance of logical data modeling in requirements
When to use logical data models
Relationship between logical and physical data model
Elements of a logical data model
Read a high-level data model
Data model prerequisites
Data model sources of information
Developing a logical data model

2. Project Context and Drivers

Importance of well-defined solution scope
Functional decomposition diagram
Context-level data flow diagram
Sources of requirements
Functional decomposition diagrams
Data flow diagrams
Use case models
Workflow models
Business rules
State diagrams

3. Conceptual Data Modeling

Discovering entities
Defining entities
Documenting an entity
Identifying attributes
Distinguishing between entities and attributes

4. Conceptual Data Modeling-Identifying Relationships and Business Rules

Model fundamental relationships
Cardinality of relationships
One-to-one
One-to-many
Many-to-many
Is the relationship mandatory or optional?
Naming the relationships

5. Identifying Attributes

Discover attributes for the subject area
Assign attributes to the appropriate entity
Name attributes using established naming conventions
Documenting attributes

6. Advanced Relationships

Modeling many-to-many relationships
Model multiple relationships between the same two entities
Model self-referencing relationships
Model ternary relationships
Identify redundant relationships

7. Completing the Logical Data Model

Use super types and subtypes to manage complexity
Use super types and subtypes to represent rules and constraints

8. Data Integrity through Normalization

Normalize a logical data model
First normal form
Second normal form
Third normal form
Reasons for denormalization
Transactional vs. business intelligence applications

9. Verification and Validation

Verify the technical accuracy of a logical data model
Use CASE tools to assist in verification
Verify the logical data model using other models
Data flow diagram
CRUD matrix