Choosing Data Stores

Basics of Data Warehouses

First, you will study the basic principles: the differences between OLTP (Operational Transactional Systems) and OLAP (Analytical Systems), and the scenarios in which they are used. You will also learn what ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) are and how these methods relate to the choice of data warehouses. At the end of the section, I will share a resource where you can further explore the types of data warehouses and compare them with each other.

Relational Databases

We will go through a step-by-step guide to selecting the appropriate data storage that you can use in your work. Then, we will take a closer look at relational databases: you will learn about the principles of CRUD and ACID, as well as get acquainted with examples of specific DBMS.

NoSQL Databases

Here you will learn what NoSQL is, what types of such databases exist (document-based, columnar, temporal, search), their characteristics, and the tasks for which they are suitable. We will also discuss the trade-offs between read and write speed and the importance of setting goals when choosing storage.

Data Warehouses and Data Lakes

At the end of the course, you will learn what data warehouses (Data Warehouses) and data lakes (Data Lakes) are, the differences between them, and the specific cases for using each solution.