Best Resources To Learn Data Engineering

Do you find yourself stuck in the masses of information available for Data Engineers on the wide web? Fret not, you’re definitely not alone in this community as there truly is a lot going on. Today, we’ll be covering some of the best resources to learn Data Engineering and get started the right way.

The KCE Process of Becoming a Data Engineer

Before we move on to answering questions like “what should I learn to become a data engineer” – there’s one more important question. How should you be learning to maximize your knowledge gain while making sure you’re on the right pathway?

Let us fit the KCE process of learning to Data Engineering here. We are sure that you would have heard from us about KCE process either in our ML Academy classes or in our other posts. KCE process stands for Knowledge, Certification and Expertise.

Focus on gaining sound knowledge of the domain you’re studying for i.e., Data Engineering
Certify yourself to governing bodies and attain certifications to show your potential and demonstrate your learning
Have expertise of solving low-end to complex business problems using the domain knowledge

Moving forward, we’ll collectively be discussing the three points as your ‘learning’ phase. The best possible way to attain all three points above is to do something practically. In the realm of Data Engineering, this could be solving a problem of integrating multiple data sources via pipelines or something you’re personally dealing with.

Point being – learn by doing.

Secondly; try not to delve into passive videos.

Sure, some of the best resources to learn Data Engineering might be passive sources like books or recorded videos. But there’s an issue here – you won’t feel as motivated to reach the end by yourself as you would if you were under someone’s direct training.

If you’ve guessed already; we’re talking about live mentorships or trainings.

A great mentor can help you maximize your learning potential. Find yourself a mentor or trainer with a proven track record of training fellow Data Engineers.

Ask people already in the industry, converse over professional platforms like LinkedIn, see if you can discover great trainers by yourself. Not to mention; you get unrestricted support from such fellows if you find some concepts hard to grasp or practically perform.

If you weren’t able to find any, take a look at our courses on ML Academy to help you out. The benefit of attending these cohorts of trainers is twofold; you can practice the art of self-discipline by sticking to a schedule and engage in a fun and beneficial learning experience with other students of the same experience level.

Also Read: How Do I Start A Career in Data Engineering?

Other Resources to Learn Data Engineering

We strictly believe the best resources to learn Data Engineering lie within a live class by a mentor. But again; there’s no harm in choosing the other way round. If you prefer reading books and can engage yourself in a strict study plan, here’s our list of the best resources for data engineering students to get started:

Courses

Several authors publish their courses online on several topics from the Data Engineering world. Though we can’t cover them all, here’s a list of some of the best resources which you can use to get started:

The Ultimate MySQL Bootcamp on Udemy
Introduction to Data Engineering by Datacamp
Python for Everybody by University of Michigan on Coursera
Data Warehousing Concepts: Basic to Advance on Udemy

Books

If you’re a fan of reading, there are hundreds of Data Engineering books in the field of Data Engineering too. Here’s a list of a few Data Engineering books you can use to get started:

Podcasts

Fellow podcast lover? It’s your turn. We all love podcasts and they’re definitely great for listening content passively while on the road or in leisure time. Here’s our list of the best podcasts for Data Engineering learners:

Blogs

Blogs are yet another great resource to learn and understand the concepts of Data Engineering. Though sparse and available in a large quantity, the best ones include:

Life of a Data Engineer: What Tools do Data Engineers Use?

Now that we’re past discovering the best resources to learn Data Engineering, let’s dive into the life of a Data Engineer. What tools do Data Engineers use? How much expertise is required? So many questions!

Here’s an extensive list of tools used by majority of engineers employed all over the globe:

Scripting and Programming
1. Python
2. Scala
3. Bash or PowerShell (automation)
Databases
1. SQL (Oracle, DB2)
2. NoSQL (MongoDB)
Cloud Infrastructure
1. AWS
2. Google Cloud (GCP)
3. Microsoft Azure
Data Collection and Ingestion Tools
1. Kafka
Data Processing Platform
1. Apache Spark
Data Engineering Framework (Data Lakes)
1. Apache Hadoop
  1. Hive
  2. Pig
  3. HDFS
Data Visualization and Reporting
1. Tableau
2. D3.JS (library)

Although this list doesn’t cover each and every tool used by Data Engineers; you can get the gist of it. Ideally, the best resources to learn Data Engineering should cover these tools. If not, you’re not moving forward in the right direction. Make sure to incorporate some or all of these in your learning pathway!

Conclusion

We’re going to conclude our article on the best resources to learn Data Engineering. We hope you’ve learned the ideal process to learn and get started with this emerging field of engineering.

Our first and ideal approach is to select a mentor with a proven record of teaching Data Engineering. Secondly, you can opt for the resources shared in the second section. There’s everything from Big Data Engineering books to the most engaging podcasts on the topic.