Learn about the world of data engineering with an overview of all its relevant topics and tools!
Have you heard people talk about data engineers and wonder what it is they do? Do you know what data engineers do but you're not sure how to become one yourself? This course is the perfect introduction. It touches upon all things you need to know to streamline your data processing. This introductory course will give you enough context to start exploring the world of data engineering. It's perfect for people who work at a company with several data sources and don't have a clear idea of how to use all those data sources in a scalable way. Be the first one to introduce these techniques to your company and become the company star employee.
Introduction to Data Engineering
-In this first chapter, you will be exposed to the world of data engineering! Explore the differences between a data engineer and a data scientist, get an overview of the various tools data engineers use and expand your understanding of how cloud technology plays a role in data engineering.
Data engineering toolbox
-Now that you know the primary differences between a data engineer and a data scientist, get ready to explore the data engineer's toolbox! Learn in detail about different types of databases data engineers use, how parallel computing is a cornerstone of the data engineer's toolkit, and how to schedule data processing jobs using scheduling frameworks.
Extract, Transform and Load (ETL)
-Having been exposed to the toolbox of data engineers, it's now time to jump into the bread and butter of a data engineer's workflow! With ETL, you will learn how to extract raw data from various sources, transform this raw data into actionable insights, and load it into relevant databases ready for consumption!
Case Study: DataCamp
-Cap off all that you've learned in the previous three chapters by completing a real-world data engineering use case from DataCamp! You will perform and schedule an ETL process that transforms raw course rating data, into actionable course recommendations for DataCamp students!