Data Warehouse Modeling and Design

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Data Warehouse Modeling and Design

Course Introduction

Data Warehouse is a critical component in any organization today, as the center and a core component of the business KPIs (Key performance indicators), which decision-making process totally depends on the insights and quality of data available in it.

Learning Data Warehouse concepts and modeling techniques is a crucial skill for any data engineer or data scientist, and to learn how to interpret the information inside Data Warehouse tables.

 

What you will learn

  • Understand the use of a Data Warehouse
  • Understand the core concepts of a Data Warehouse
  • Understand the Dimensional Modeling
  • Understand different types of Facts
  • Understand different types of Dimensions
  • Understand different types of measures

Who should take this course

Any data science, data engineer, data analyst, and anyone interested to learn about the Data Warehouse and its components.

Introduction

1
Why do we need Data Warehouse – Part 1
5 Minutes
2
Why do we need Data Warehouse – Part 2
6 Minutes
3
Data Warehouse Charactersitics
3 Minutes
4
Data Warehouse – Conclusion
2 Minutes
5
Data Warehouse Introduction Quiz
2 questions

Dimensional Modeling Introduction

1
Dimensional Modeling Introduction
7 Minutes
2
ER vs Dimensional
7 Minutes

Dimension Keys

1
Natural Key
4 Minutes
2
Surrogate Keys
2 Minutes
3
Durable Keys
3 Minutes

Dimensions

1
Conformed Dimension
2 Minutes
2
Role-Playing Dimension
2 Minutes
3
Junk Dimension
2 Minutes
4
SCD- Type 0 – Type 1
4 Minutes
5
SCD Type 0 – Conclusion
6
SCD Type 1 – Conclusion and Use Cases
7
SCD Type 2
6 Minutes
8
SCD Type 2 – Conclusion and Use Cases
9
SCD Type 3
3 Minutes
10
SCD Type 3 – Conclusion and Use Cases
11
SCD Type 6
6 Minutes
12
Dimensions Best Practice Tip
13
Dimensions Knowledge Check
7 questions

Facts

1
Facts Introduction – Grain
6 Minutes
2
Transactional Fact
2 Minutes
3
Transactional Fact Table – Conclusion and Use Cases
4
Periodic Snapshot Facts
2 Minutes
5
Periodic Snapshot Facts – Conclusion and Use Cases
6
Accumulating Facts
3 Minutes
7
Accumulating Facts – Conclusion and Use Cases
8
Factless Fact
2 Minutes
9
Factless Fact Table – Conclusion and Use Cases
10
Handle Null Value
4 Minutes
11
Different Fact Types in the same Model
2 Minutes
12
Facts Knowledge Check
3 questions

Measures

1
Additive
5 Minutes
2
Non-Additive
3 Minutes
3
Semi-Additive
4 Minutes
4
Measures Knowledge Check
1 question
Any data science, data engineer, data analyst, and anyone interested to learn about the Data Warehouse and its components.
- Understand the use of a Data Warehouse - Understand the core concepts of a Data Warehouse - Understand the Dimensional Modeling - Understand different types of Facts - Understand different types of Dimensions - Understand different types of measures
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Enrolled: 35 students
Duration: 3 Hours
Lectures: 35
Video: 2 Hours