One part of creating a data platform and pipelines is to choose data stores, which is the topic of this course.
Here, we will look into relational databases and NoSQL databases as well as data warehouses and data lakes. This way, you learn when to use the different databases and storages and how to incorporate them into your pipeline.
After this course you know how to store your data and how to actually choose the right data storage for your purpose. It helps you to understand the differences between the storage types and to make good decisions in your future work as a Data Engineer. In later courses I will also apply specific data stores out of the different categories.
Data Stores Basics
First of all, I will give you some basics at hand. You learn the difference between Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP) and understand for which jobs you need which technique. Also you learn what is behind Extract Transform Load (ETL) and Extract Load Transform (ELT) and how this is linked to your databases and stores. At the end of this section, l give you a resource at hand where you can find out more information on the many different types of data stores and how they are ranked.
You learn how to choose the right data stores for your purposes by going through a step-by-step guide. This you can apply any time when it comes to choosing the ideal data storage. Afterwards we dig a bit deeper into relational databases and their features. I will explain to you the concepts of CRUD and ACID and also have a look at some database examples.
I will talk about NoSQL databases, their features and important types, such as document stores, wide column stores, time series and search engines. You also learn about tradeoffs between read and write performance and why setting your own goals is so important.
Data Warehouses & Data Lakes
In the end, I will explain to you what data warehouses and data lakes are. This way, you understand what these tools are used for and in which situation you should use them.