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A little over a year ago, the SparkED team set out to deliver a comprehensive course that would expose learners to key concepts in the world of data. We envisioned interactive lessons that would compile years of real-world experience into a truly introductory course. We wanted to make a course that was product agnostic and described the greater data landscape. We also knew that many people who watched would already feel comfortable with certain topics, so we tried to make the lessons as independent as possible. Figuring out how to cram all that information into independent lessons was tough, but after a year of development, we’re proud to say that the entire Data Essentials course is now live on Alteryx Community!


You may be wondering what exactly is covered in this course. The answer is, “A lot!” While we left some ideas on the cutting room floor, we tried to be as holistic as possible (without making the development period two years). Let’s take a look at what each lesson focuses on…


In the first lesson, Decisions with Data, we talk about why data is critical to both individuals and organizations. This brief video lays the foundation of why you might want to learn about data…and take the rest of the lessons. 😉




Defining Data is the second lesson in the series. The aptly named lesson describes what counts as data, introduces the concept of datatypes and metadata, then touches on visualizing data. These concepts are at the heart of data analysis, so this lesson is a must for any beginner.


The third lesson in the course is Data and Devices, which is a bit of a departure from the standard data analytics material. We discuss the basic hardware components of devices, then shift to a focus on the software that brings those devices to life. For good measure, we touch on some basics of computer languages and coding.


Database-ics was just too good to pass up. Most people have heard the term database and feel comfortable thinking about it as a data storage option, but as we get into data analytics, we may or may not get brought up to speed on how they work and the variety of database options that exist. This lesson describes why databases are used in lieu of flat files, and it touches on the difference between relational and non-relational options. It also covers data warehouses and data lakes to make sure we’re all on the same page.




Lesson five is all about Data in the Cloud. Like databases, most folks have preconceptions about what the cloud is, but that isn’t enough when we need to perform analytics in the cloud. This is a big topic and will only become more critical in the future, so we start with the basics to ensure that subsequent cloud materials stick in your brain! We talk about some networking basics, IP addresses, servers, and APIs to give you a better idea of what’s happening in your vendor’s data center.


Intro to Data Analytics takes us back to the heart of data analysis by describing the conceptual tasks that are most commonly performed when analyzing data. The lesson also introduces some common language around these processes, like ETL, AI, and ML.


The course finishes with the seventh lesson on Data Stewardship. This lesson examines some of the key considerations when using data from an organizational and analyst perspective. Topics include Data Governance, Data Ethics, Bias, and more…


While those brief descriptions don’t lay out everything that’s covered in the course, they do illustrate the variety of topics included. The course isn’t designed to train analysts but rather provide a better understanding of concepts and terminology that will crop up in any data/analytics career. After taking this course, viewers are well placed to continue learning with hands-on training in a specific area or product (like the Getting Started Learning Path). We hope you enjoy the course and learn something along the way!