CF

Relational Data Modeling

1h 52m
English
Paid

Relational modeling is widely used in the construction of transactional databases. You might say, "But I'm not planning to become a backend engineer." However, knowing not only how to move data, but also how to effectively store it, is a key skill. This includes creating a scalable data structure that ensures fast query processing and efficient data retrieval.

Ensuring Data Quality and Integrity

Besides performance, the relational model must ensure data quality and integrity through the use of constraints, primary and foreign keys, validation, and relationships between tables.

What You Will Learn

How to Design and Read a Data Model

You will get acquainted with three levels of relational modeling: conceptual, logical, and physical models. We will go through the entire process—from defining entities and attributes to building tables and relationships between them using keys and constraints.

Normalization from 0NF to 3NF

You will learn how to normalize data to avoid duplication and enhance integrity. We will step through the first, second, and third normal forms and explain how to apply them when building a database.

Deploying a MySQL Server Using Docker

In practice, you will learn to deploy MySQL as a container using Docker. We will also discuss alternative approaches, including local installations and cloud services.

Working with MySQL Workbench

You will install and use MySQL Workbench—one of the most popular GUI clients for working with MySQL. As part of the practice, you will create an ER diagram of a database using built-in modeling tools.

This course is an excellent start for those who want to think in terms of data structure, design databases “smartly,” and use best modeling practices.

About the Author: Eka Ponkratova

Eka Ponkratova thumbnail

Eka Ponkratova is a data engineer and educator focused on the modeling side of data warehouse construction — the dimensional and relational schema-design decisions that lock in early in a data warehouse's life and become expensive to change later.

Her CourseFlix listing carries two Eka Ponkratova courses: Dimensional Data Modeling (the Kimball-style star and snowflake schema patterns underneath analytical data warehouses) and Relational Data Modeling (the OLTP-side normalisation and integrity patterns). Together the courses cover both halves of a data engineer's modeling craft.

Material is paid and aimed at data engineers and analytics engineers responsible for the schema decisions in their organisation's data stack. For broader content, see CourseFlix's Data processing and analysis category page.

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#1: Introduction
All Course Lessons (17)
#Lesson TitleDurationAccess
1
Introduction Demo
02:03
2
Goals of the course
03:40
3
Relational data models history
03:17
4
Installing MySQL server and MySQL Workbench
08:05
5
MySQL Workbench introduction
04:37
6
The design process explained
04:15
7
Discover the entities
10:25
8
Discover the attributes
13:10
9
Define entity relationships and normalize the data
11:20
10
Identifying vs non-dentifying relationship
02:02
11
How to resolve many-to-many relationships
04:01
12
How to resolve one-to-many relationships
02:35
13
How to resolve one-to-one relationships
01:46
14
Create your ER diagram using workbench
19:47
15
Create a physical data model
04:14
16
Populate the mysql db with data from a .xls file
15:14
17
Course Conclusion
01:29
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Frequently asked questions

What are the prerequisites for enrolling in this course?
Prospective students should have a basic understanding of databases and some familiarity with SQL. Prior experience with Docker and MySQL would be beneficial, though not strictly necessary, as the course covers installing MySQL server and MySQL Workbench.
What specific skills will I gain from this course?
Students will learn how to design and read a data model across conceptual, logical, and physical levels. The course covers normalization techniques from 0NF to 3NF, deploying MySQL using Docker, and utilizing MySQL Workbench. It emphasizes ensuring data quality and integrity using constraints, keys, and relationships.
Who is the target audience for this course?
This course is ideal for individuals interested in database design and management, including aspiring data engineers and analysts. It's also suitable for those who want to understand data storage and retrieval, even if they do not plan to become backend engineers.
How does this course compare to other database courses?
Unlike courses that focus solely on SQL querying, this course delves into the design aspects of databases, including relational modeling and normalization. It provides practical skills in deploying and managing MySQL servers, setting it apart from introductory SQL courses.
What database management tools will I learn to use?
You will learn to use MySQL Workbench, a popular GUI client for MySQL, and deploy MySQL servers using Docker. The course also touches upon alternative approaches like local installations and cloud services.
Is there any topic that this course does not cover?
The course does not cover advanced SQL query optimization or non-relational database systems. It focuses specifically on relational data modeling, normalization, and using MySQL tools.
How much time should I expect to commit to this course?
The course consists of 17 lessons. While the total runtime is not specified, students should allocate time for both theoretical lessons and practical exercises, such as deploying MySQL servers and creating ER diagrams.