Description

Data-modelling-real-world-complexities is based on the notion of real-world entities and relationships among them. It creates an entity set, a relationship set.

Course Content 

1-Introduction

• Data Modeling Fundamentals
• The Purpose and Role of Data Modeling
• Basic Data Modeling Concepts and Terminology
• Navigate Your Alternatives Among Methodologies, Techniques, and Notations
• Compare Data Modeling to Database Design
• Compare Transactional Data Modeling to Analytical Data Modeling
• Summarize Data Modeling Fundamentals

2-Building Blocks of Data Modelling

• Introducing Data Modeling Building Blocks
• The role of Entities in Data Modelling
• Add Attributes to Your Data Model
• Use Multi-Valued Attributes in Your Data Model
• Build Relationships into Your Data Model
• Summarize Data Modeling Building Blocks
• Basic Data Modelling

3-Real-world Complexities to entities and Attributes

• Why Real-World Complexities Matter in Data Modeling
• Build Hierarchies for the Entities in Your Data Model
• Specify Constraints for Your Attributes
• Specify Cross-Entity Dependencies Through Strong and Weak Entities
• Summarize Real-World Entity and Attribute Complexities
• Entity and Attribute Constraints

4-Real-world Complexities to Relationship

• Why Relationship Cardinality and Complexities Matter
• Build Real-World Complexities into Data Model Relationships
• Define the Maximum Cardinality of a Relationship
• Define the Minimum Cardinality of a Relationship
• Use Crow’s Foot Notation for Minimum and Maximum Cardinality
• Summarize Cardinality and Complex Relationships

5-Move across the different levels of Data Model

• Harmonize Different Levels of a Data Model
• A Brief Look at Relational Database Normalization
• Forward-Engineering Your Conceptual Data Model
• More Data Model Forward-Engineering
• Reverse-Engineer a Physical Model Back into a Conceptual Model
• Summarize How to Work with Different Levels of a Data Model

6-Software for Data Modelling

• The Importance of Data Modeling Software
• Build a Data Model with a Drawing Program
• Build a Model with a Data Modelling Software Tool

7-Mandatory, Optional Sub-type Recursive

• Relational Model & Normalization principles(1NF,2NF,3NF)
• Relational Algebra & SQL
• Dimensional modeling approach
• Inmon v/s Kimball approach
• Dimensional modeling steps
• Star & snowflake schema
• Fact table techniques
• Dimension table techniques
• Slowly changing dimensions

8-Architect Data Modeler

• Data Modeling and diagram visualization techniques
• ER Diagrams
• Instant SQL
• Data Robot
• Forward & Reverse Engineering
• Model Comparison
• Reporting & Publishing
• Dimensional Modelling

Locus Academy has more than a decade experience in delivering the training/staffing on Data Modelling for corporates across the globe. The participants for the training/staffing on Data Modelling are extremely satisfied and are able to implement the learnings in their on going projects.