It seems like it might be finally happening.
Data engineering is finally getting a little bit of the data lime light.
Which makes sense.
The data being stored and analyzed is not only becoming more voluminous but its speed, complexity and variety are also increasing. Making it difficult to wrangle.
With all this new data comes new tools, best practices and methods to manage and optimize the data systems we rely on.
While I've been working as a consultant for years as the Seattle Data Guy, I'm still constantly learning and reviewing the best data engineering courses to improve my skills and understanding. Check out these highly-rated courses I've enjoyed and consider which ones might be best for the next step in your career.
Don't let the number of courses available online overwhelm you. If you're not sure where to start, or you're taking far too many courses at the same time like I am, then look for a course that offers these features.
There's a whole world of Microsoft stack, SQL, and web service tools that you use or will use in your career. Some great online data engineering courses to start with give you a hands-on and theoretical understanding of these basic tools.
Detailed explanations of basic tools can be a great starting point, but you'll soon feel overwhelmed without more high-level concepts and an understanding of the architecture of your project. __
There are plenty of options when it comes to learning about data engineering. But first, you need to decide if you like the kind of work data engineers do. So I recommend looking towards some of the free youtube channels that discuss the concepts and tools data engineers use. I will reference two of them below. But I just wanted to call out this tip before we go too deeply in to my top data engineering courses.
Most online course systems have rated and visible attendance statistics. Platforms like Udemy and Coursera make it easy to find compelling courses. Just because a course is well attended or rated doesn't mean it's going to offer you the skills you need, but this is a helpful feature to compare.
I've taken many online courses over the years, but these six options are some of the best data engineering courses to start with:
This free video tutorial series is packed with helpful information to create a baseline knowledge in Microsoft tooling such as SQL Server, SSIS and more. Brush up on the basics or start your journey with WiseOwl tutorials as a good primer.
Check out tutorials on SQL and ETL tools. These videos can help you learn how to drag and drop destinations and transformations into your workspace. The SQL playlist is a good jumping-off point for these skills.
Everyone likes a free course, but there are a few features missing in these playlists. I don't like that it doesn't go into much detail about why you need to perform particular actions. This high-level architecture is a key piece of the puzzle that you'll need to use as an engineer.
Another free option is the Apache Airflow Youtube tutorial series. This series is seven videos long and will give you a great baseline of Airflow.
It goes over the basic features of Airflow, which is used to improve the traditional view of ETL. Many professionals use this tool to create hundreds and thousands of pipelines in a more manageable way. You'll learn more about Airflow DAG and get ready to create your first pipeline.
Like the WiseOwl tutorials, this series tends to focus more on the specific steps of using a tool, rather than the overarching reason. It's a great place to start, but be sure you gain that higher-level understanding before you head out into the field as an engineer.
The first paid course on my list, the Data Warehouse Fundamentals for Beginners Udemy course is a great way to explore the best practices and high-level concepts of architecture and dimensional design in a convenient course offering.
It's no wonder this course is a bestseller; it does a great job of explaining how to use ETLs and warehouses. It explores the skills you need, like building staging layers, fact tables, and dimension tables, but also explains the schemas and frameworks of these tools.
A great addition to this course is the information on slowly changing dimensions. This allows you to not only copy a database but to add context and track it historically.
Big data concepts and web services tools are all important to learn about. Brush up on these areas with the Big Data on Amazon Web Services Udemy course. This course is more expensive than other offerings, but Udemy typically offers a discount on it.
The focus of this course is AWS, so the tool-specific steps may not translate well to other cloud-based models. The theoretical concepts, however, are going to be very similar if you're using GCP or Azure.
You'll need to dedicate more time to this course since the videos tend to run a little longer. Some videos are between 15 to 18 minutes long, which I feel is slightly longer than ideal. Take notes along the way to stay on track.
You can't go wrong with a course from Frank Kane. The Taming Big Data Udemy course is a personal favorite, but many of his courses are helpful and highly rated.
This training gives you building blocks and practice tasks in Spark and Python. There will always be an adjustment going from the classroom to real-world applications, but Frank Kane does a great job bridging some of that gap and helping you see how these tools work in real problems.
This area of design is popular in the field, so add this to your online course list. On Coursera, Introduction to Designing Data Lakes on AWS gives you big-picture concepts and more specific skillsets on data lake creation and operation.
Like most Coursera classes, the first week is very general and could be skipped, but the second week kicks off the course with information about AWS and data lake architecture. It's more specific than other big data courses, so it's a good addition to the list.
These data engineering courses will give you a 3-to-6-month crash course if not longer. So don't rush.
Take your time and learn the basics. Get your base level of data engineering skills down and then once you start working you will find lots of opportunities to challenge yourself with new problems.
But, if you are looking for new opportunities to learn now, then our team is working on an article for applying your data engineer skills to data engineer projects.
I'm always looking for new courses to take and to pass on to other professionals, so feel free to contact me with any questions or course recommendations. Start with WiseOwl tutorials or go through these top six courses in your own way to improve your skills and conceptual knowledge.
Thanks for reading! If you want to read more about data consulting, big data, and data science, then click below.