Data Warehouse – The Ultimate Guide

Data Warehouse – The Ultimate Guide, available at $99.99, has an average rating of 4.58, with 102 lectures, 9 quizzes, based on 6979 reviews, and has 45019 subscribers.

You will learn about 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 This course is ideal for individuals who are Data Analyst that want to upskill and learn how to build a data warehouse or Data Engineers that want to learn about data warehousing and data modeling or People that want to become a data architect, BI consultant, data engineer or data analyst or Data professionals that want to upskill in Business Intelligence & Data Modeling It is particularly useful for Data Analyst that want to upskill and learn how to build a data warehouse or Data Engineers that want to learn about data warehousing and data modeling or People that want to become a data architect, BI consultant, data engineer or data analyst or Data professionals that want to upskill in Business Intelligence & Data Modeling.

Enroll now: Data Warehouse – The Ultimate Guide

Summary

Title: Data Warehouse – The Ultimate Guide

Price: $99.99

Average Rating: 4.58

Number of Lectures: 102

Number of Quizzes: 9

Number of Published Lectures: 102

Number of Published Quizzes: 9

Number of Curriculum Items: 113

Number of Published Curriculum Objects: 113

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

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

Who Should Attend

Data Analyst that want to upskill and learn how to build a data warehouse
Data Engineers that want to learn about data warehousing and data modeling
People that want to become a data architect, BI consultant, data engineer or data analyst
Data professionals that want to upskill in Business Intelligence & Data Modeling

Target Audiences

Data Analyst that want to upskill and learn how to build a data warehouse
Data Engineers that want to learn about data warehousing and data modeling
People that want to become a data architect, BI consultant, data engineer or data analyst
Data professionals that want to upskill in Business Intelligence & Data Modeling

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!

Course Curriculum

Chapter 1: Intro

Lecture 1: Welcome!

Lecture 2: How this course works

Lecture 3: What do you learn in this course?

Lecture 4: Course slides

Chapter 2: Data Warehouse Basics

Lecture 1: Why a data warehouse?

Lecture 2: What is a data warehouse?

Lecture 3: What is Business Intelligence?

Lecture 4: Data Lake or Data Warehouse?

Lecture 5: Setting up Pentaho (ETL tool)

Lecture 6: Demos & Hands-on

Lecture 7: Pentaho for Mac M1/M2: Installation & Troubleshooting

Lecture 8: Setting up PostgreSQL (Database system)

Chapter 3: Data Warehouse Architecture

Lecture 1: 3 Layers of a Data Warehouse

Lecture 2: Staging area

Lecture 3: Demo: Setting up the staging area

Lecture 4: Data Marts

Lecture 5: Relational databases

Lecture 6: In-Memory databases

Lecture 7: Cubes

Lecture 8: Operational Data Storage

Lecture 9: Summary

Chapter 4: Dimensional Modeling

Lecture 1: What is dimensional modeling?

Lecture 2: Why dimensional modeling?

Lecture 3: Facts

Lecture 4: Dimensions

Lecture 5: Star schema

Lecture 6: Snowflake schema

Lecture 7: Demo: Product & Category dimension (snowflaked)

Chapter 5: Facts

Lecture 1: Additivity

Lecture 2: Nulls in facts

Lecture 3: Year-to-Date facts

Lecture 4: Types of fact tables

Lecture 5: Transactional fact tables

Lecture 6: Periodic fact tables

Lecture 7: Accumulating snapshots

Lecture 8: Comparing fact table types

Lecture 9: Factless fact tables

Lecture 10: Steps in designing fact tables

Lecture 11: Surrogate Keys

Lecture 12: Case Study: The Project

Lecture 13: Case Study: Identify the business process

Lecture 14: Case Study: Define the grain

Lecture 15: Case Study: Identify the facts

Lecture 16: Case Study: Identify the dimensions

Chapter 6: Dimensions

Lecture 1: Dimension tables

Lecture 2: Date dimensions

Lecture 3: Nulls in dimensions

Lecture 4: Hierarchies in dimensions

Lecture 5: Conformed dimensions

Lecture 6: Degenerate dimensions

Lecture 7: Junk dimension

Lecture 8: Role-playing dimension

Lecture 9: Case Study: Date dimension

Chapter 7: Slowly Changing Dimensions

Lecture 1: What are slowly changing dimensions?

Lecture 2: Type 0 – Original

Lecture 3: Type 1 – Overwrite

Lecture 4: Type 2 – Additional row

Lecture 5: Administrating Type 2 dimensions

Lecture 6: Mixing Type 1 & Type 2

Lecture 7: Type 3 – Additional attribute

Chapter 8: ETL process

Lecture 1: Understanding the ETL process

Lecture 2: Extract

Lecture 3: Initial Load

Lecture 4: Delta Load

Lecture 5: Load Workflow

Lecture 6: Demo: Quick Intro to Pentaho

Lecture 7: Demo: Setting up tables in SQL

Lecture 8: Demo: Initial Load example

Lecture 9: Demo: Delta Load example

Lecture 10: Transforming data

Lecture 11: Basic Transformations

Lecture 12: Advanced Transformations

Lecture 13: Demo: Planning next steps

Lecture 14: Demo: Table setup & Complete Staging

Lecture 15: Demo: Transform

Lecture 16: Demo: Load & Validate results

Lecture 17: Scheduling jobs

Chapter 9: ETL tools

Lecture 1: ETL tools

Lecture 2: Choosing the right ETL tool

Chapter 10: Case Study: Creating a Data Warehouse

Instructors

Nikolai Schuler
Building Better Data Careers

Rating Distribution

1 stars: 39 votes
2 stars: 63 votes
3 stars: 464 votes
4 stars: 2408 votes
5 stars: 4005 votes

Frequently Asked Questions

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