https://www.udemy.com/course/master-data-modeling-with-erwin-data-modeler-tool

What you'll learn: 

Relational Data Modeling

Dimensional Data Modeling

Erwin Data Modeling Tool

Practice Sessions on Data Modeling

Requirements:

No prior experience in Data Modeling. Anyone working with data can take this course.

Description:

In this course we will learn Data Modeling and explore how to use erwin data modeling tool effectively. This course is very extensive around 10 hours and we will cover almost every data modeling concept with proper examples. We will also cover use of erwin data modeler along with related data modeling concepts. We have tried to keep data modeling theory lectures and erwin hands on lectures combined so you not only understand the theory but also practical implementation. Learning Data Modeling is an extensive journey which requires proper theoretical knowledge and also lot of hands-on practice.

We have put lot of efforts to create this course interesting, simplified and knowledgeable and I am sure... you will also take this course with full of dedication.

In this course, we will cover below topics,

· Introduction to course (Theory)

· Why Data Modeling (Theory)

· Why Erwin (Theory)

· Who can use this course (Target Audience) (Theory)

· How to use this course effectively (Theory)

· erwin Data Modeler User Interface (Erwin)

· Overview of Data Modeling (Theory)

· Overview of ER Model (Theory)

· Entities (Theory)

· Entities from erwin (Erwin)

· Datatypes (Theory)

· Attributes (Theory)

· Attributes from erwin (Erwin)

· Relationships (Theory)

· Relationships from erwin (Erwin)

· Keys (Theory)

· Keys from erwin (Erwin)

· Supertypes & Subtypes (Theory)

· Supertypes & Subtypes from erwin (Erwin)

· Create a simple data model + erwin (Practice)

· Notations (Theory)

· Naming Standards (Erwin)

· Define Domains (Erwin)

· Data Modeling Template (Erwin)

· Create a simple data model for IMDB (Practice)

· Conceptual Data Model (Theory)

· Conceptual Data Model erwin (Erwin)

· Logical Data Model (Theory)

· Logical Data Model erwin (Erwin)

· Normalization (Theory)

· Physical Data Model (Theory)

· Physical Data Model erwin (Erwin)

· "Physical Data Model erwin :-

· Forward Engg (Erwin)"

· Database connection (Theory)

· "Physical Data Model erwin :-

· Reverse Engg (Erwin)"

· Complete Compare (Erwin)

· Dimensional Modeling (Theory)

· Types of Dimension & Fact tables (Theory)

· Dimensional Modeling Erwin (Erwin)

· Data Warehousing (Theory)

· Data Warehousing Approaches (Theory)

· Data Warehousing from erwin (Erwin)

· "Difference between Dimensional Modeling &

· Relational Modeling (Theory)"

· Denormalization (Theory)

· Denormalization Erwin (Erwin)

· Data Modeling Approach (Theory)

· Create a Dimensional data model for Amazon (Theory)

· Amazon Model - Part 1 (Practice)

· Amazon Model - Part 2 (Denormalization) (Practice)

· Data Model Properties (Erwin)

· erwin Transformation (Erwin)

· Subject Area (Erwin)

· Diagram (Erwin)

· Design Layers (Erwin)

· Macros (Erwin)

· Report Designer (Erwin)

· Source to Target mapping in erwin (Erwin)

· Bulk Eduítor - Update Table Definition (Erwin)

· Bulk Eduítor - Update Column Definition (Erwin)

· Query Tool (Erwin)

· Saving the Data model (Erwin)

· Importance of Data Modeling (Theory)Who this course is for:Developer or Tester working in OLTP or OLAP or DSS systems, Students learning database management etc.

Who this course is for:

Developer or Tester working in OLTP or OLAP or DSS systems, Students learning database management etc.