Mô tả

Master Data Warehousing, Dimensional Modeling & ETL process

Do you want to learn how to implement a data warehouse in a modern way?

This is the only course you need to master architecting and implementing a data warehouse end-to-end!


Data Modeling and data warehousing is one of the most important skills in Business Intelligence & Data Engineering!

This is the most comprehensive & most modern course you can find on data warehousing.


Here is why:

  • Most comprehenisve course with 9 hours video lectures

  • Learn from a real expert - crystal clear & straight-forward

  • Master theory & practice - hands-on demonstrations, assignments & quizzes

  • We will implement a complete data warehouse - end-to-end

  • Understand everything step by step from the absolute basics to the advanced topics

  • Learn the practical steps and the important theory to upskill your career

This course will take you all the way to being able to architect and implement a data warehouse in a company in a professional manner.


Here is what you'll learn:

  • Data Warehouse Basics

  • Data Warehouse architecture

  • Data Warehouse infrastructure

  • Data Modeling

  • Setting up an ETL process

  • Dimensional Modeling: Facts & Dimensions

  • Implementing a comeplete data warehouse hands-on

  • Slowly Changing Dimensions

  • Understanding ETL tools

  • ELT vs. ETL

  • Advanced topics like: Columnar storage, OLAP Cubes, In-memory databases, massive parallel processing & cloud data warehouses

  • Optimizing a data warehouse using indexes (B-tree indexes & Bitmap indexes)

  • Practically using and connecting a data warehouse


By the end of this course you will be able to design & build a complete data warehouse from the ground up. You will have the knowledge, the practical skills and the confidence to implement a modern data warehouse professionally.

Everything you need to be a highly proficient data architect, data engineer, data analyst or Business Intelligence expert!


Join now to get instant & lifetime access - of course backed by the no-questions-asked 30 days money back guarantee!




Bạn sẽ học được gì

Architect & implement a professional data warehouse end-to-end

You will learn the principles of Data Warehouse Design

You will master ETL process in both theory & practise

You will implement in a case study your own data warehouse & ETL process

You will learn the modern architecture of a Data Warehouse

Dimensional Modeling in a professional way

Yêu cầu

  • Basic SQL is helpful but absolutely not necessary
  • Laptop or PC

Nội dung khoá học

15 sections

Intro

4 lectures
Welcome!
02:13
How this course works
04:26
What do you learn in this course?
02:57
Course slides
00:32

Data Warehouse Basics

10 lectures
Why a data warehouse?
04:42
What is a data warehouse?
04:19
The purpose of a data warehouse
4 questions
What is Business Intelligence?
02:47
Data Lake or Data Warehouse?
06:23
Data Lake & Business Intelligence
2 questions
Setting up Pentaho (ETL tool)
03:57
Demos & Hands-on
02:40
Pentaho for Mac M1/M2: Installation & Troubleshooting
02:07
Setting up PostgreSQL (Database system)
06:35

Data Warehouse Architecture

11 lectures
3 Layers of a Data Warehouse
06:27
Staging area
07:22
Demo: Setting up the staging area
03:39
Data Marts
06:27
Staging area & Data Marts
3 questions
Relational databases
06:23
In-Memory databases
06:48
Cubes
07:47
Different database systems
2 questions
Operational Data Storage
07:29
Summary
04:29

Dimensional Modeling

10 lectures
What is dimensional modeling?
03:26
Why dimensional modeling?
04:34
Facts
05:03
Dimensions
04:26
Star schema
07:39
Snowflake schema
05:11
Demo: Product & Category dimension (snowflaked)
10:18
Facts & Dimensions (ProjectLogs)
1 question
Facts & Dimensions (SalesTransactions)
1 question
Dimensional modeling
4 questions

Facts

18 lectures
Additivity
08:28
Nulls in facts
04:01
Year-to-Date facts
03:19
Facts I
3 questions
Types of fact tables
00:32
Transactional fact tables
03:32
Periodic fact tables
03:51
Accumulating snapshots
03:34
Comparing fact table types
03:35
Identifying fact tables
2 questions
Factless fact tables
04:05
Steps in designing fact tables
04:40
Surrogate Keys
06:02
Case Study: The Project
04:37
Case Study: Identify the business process
02:05
Case Study: Define the grain
02:59
Case Study: Identify the facts
05:25
Case Study: Identify the dimensions
03:29

Dimensions

10 lectures
Dimension tables
06:24
Date dimensions
07:24
Nulls in dimensions
04:42
Hierarchies in dimensions
04:47
Conformed dimensions
05:44
Degenerate dimensions
03:40
Junk dimension
08:07
Role-playing dimension
05:57
Case Study: Date dimension
05:37
Understanding dimensions
3 questions

Slowly Changing Dimensions

8 lectures
What are slowly changing dimensions?
03:14
Type 0 - Original
01:58
Type 1 - Overwrite
03:43
Type 2 - Additional row
05:27
Administrating Type 2 dimensions
05:55
Mixing Type 1 & Type 2
02:31
Type 3 - Additional attribute
06:00
Understanding Slowly Changing Dimensions
3 questions

ETL process

17 lectures
Understanding the ETL process
06:37
Extract
03:02
Initial Load
03:16
Delta Load
06:59
Load Workflow
04:15
Demo: Quick Intro to Pentaho
09:32
Demo: Setting up tables in SQL
04:58
Demo: Initial Load example
10:05
Demo: Delta Load example
13:38
Transforming data
04:37
Basic Transformations
06:05
Advanced Transformations
07:24
Demo: Planning next steps
05:18
Demo: Table setup & Complete Staging
09:11
Demo: Transform
07:07
Demo: Load & Validate results
05:45
Scheduling jobs
05:51

ETL tools

2 lectures
ETL tools
04:42
Choosing the right ETL tool
06:03

Case Study: Creating a Data Warehouse

9 lectures
Plan of attack
02:23
Source data & table design
08:55
Setting up the tables in database
02:59
Staging: Sales Fact
07:47
Staging job & fixing problems
06:34
Load Payment Dimension
05:34
Transform & Load Sales Fact
09:26
Transform & Load job
03:10
Final ETL job & Incremental Load
06:17

ETL vs. ELT

2 lectures
What is an ELT?
05:15
ETL vs. ETL
04:54

Using a Data Warehouse

2 lectures
What are the common use cases?
04:05
Connecting the DWH to Power BI
10:22

Optimizing a Data Warehouse

5 lectures
Using indexes
05:01
B-tree indexes
02:42
Bitmap indexes
03:31
Guidelines for indexes
07:41
Demo: Setting indexes
03:56

The Modern Data Warehouses

4 lectures
Cloud vs. on-premise
02:47
Benefits cloud vs on-premise
05:50
Massive parallel processing
05:34
Columnar storage
04:19

Bonus

1 lectures
Bonus lecture
01:07

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