Dimensional Data Modeling
Course description
In today's world, where data plays a key role, effective organization of information is the foundation for quality analytics and report building. Multidimensional data modeling is an important approach that allows structuring data for quick access and informed decision-making.
This course provides a detailed introduction to the fundamental concepts of dimensional modeling. You will learn how fact and dimension tables work, what slowly changing dimensions (SCD) are, as well as the different types of fact tables.
During the course, you will gain practical experience in setting up and working with a data warehouse using real tools - DuckDB and DBeaver. By the end of the training, you will confidently understand how to design a data model for high-performance analytics and reporting.
Read more about the course
Course includes:
Introduction to Data Warehouses
You will learn the basics of building warehouses and their importance for analytical processing. Discover how a data warehouse consolidates information from various sources for fast and scalable analysis.
Basics of Dimensional Modeling
You will become acquainted with key elements: dimensional and fact tables. You will learn how to design a data structure for analytics, determine business metrics, find suitable dimensions, and link them together. Through practical examples, you will master the principles of building a meaningful and efficient data model.
Setting Up a Data Warehouse
You will learn to work with DuckDB and DBeaver: create tables, manage them, and prepare the environment for analytics. The module includes step-by-step instructions for setting up the environment and deploying your first warehouse.
Working with a Data Warehouse
Dive into advanced topics: learn to handle slowly changing dimensions (SCD), work with different types of fact tables - transactional and cumulative. You will understand how to track business events and trends, as well as optimize queries and analyze large volumes of data.
Watch Online
All Course Lessons (16)
| # | Lesson Title | Duration | Access |
|---|---|---|---|
| 1 | Introduction Demo | 01:58 | |
| 2 | Course Goals | 02:06 | |
| 3 | Intro to Data Warehousing | 06:43 | |
| 4 | Approaches to building a data warehouse | 05:21 | |
| 5 | Dimension tables explained | 05:35 | |
| 6 | Fact tables explained | 06:35 | |
| 7 | Identifying dimensions | 03:17 | |
| 8 | What is duckdb | 05:59 | |
| 9 | First DuckDB hands-on | 02:21 | |
| 10 | Creating tables in duckdb | 02:41 | |
| 11 | Installing dbeaver | 06:50 | |
| 12 | Exploring scd0 and scd1 | 19:58 | |
| 13 | Exploring scd2 | 13:53 | |
| 14 | Exploring transaction fact table | 06:29 | |
| 15 | Exploring accumulating fact table | 07:18 | |
| 16 | Conclusion | 00:53 |
Unlock unlimited learning
Get instant access to all 15 lessons in this course, plus thousands of other premium courses. One subscription, unlimited knowledge.
Learn more about subscriptionComments
0 commentsWant to join the conversation?
Sign in to commentSimilar courses
Semantic Log Indexing & Search
Case Study in Product Data Science
Python for Data Engineers
2022 Python for Machine Learning & Data Science Masterclass
