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I’m an Alteryx sales engineering manager who also teaches a course called Business Applications of Data Science at the University of California, Irvine extension campus. I often notice that my students who are new to the data analytics field arrive with a feeling of uncertainty about the topic.
Perhaps due to a lack of exposure to the field, or a lack of belief in themselves, many doubt their fit for a job role in our data-driven business world. They worry that data analytics will require them to do a ton of math or be really good with databases.
But I emphasize for all my students that data analytics is a team sport with lots of roles. You have someone who prepares the data, you have a data engineer, you have someone who’s really good at visualization, and another who’s good at ETL (extract-transform-load).
I tell them that at Alteryx, we like to say you don’t have to be a data scientist to have data breakthroughs. And you can actually see their eyes opening up to the possibilities.
It’s awesome to equip these students with basic data skills, some hands-on experience, and show them how to find the golden nuggets – it makes them feel powerful. These same students tend to leave the course with enough confidence to take on the world.
My course is the first in UC Irvine’s certificate program for data analytics. It focuses on the practical applications—the near-infinite number of use cases where data can be used to generate insights or solve difficult business challenges.
For example, how can an oil and gas company use data to prevent an oil rig accident? Can a bakery reduce bread waste with a camera mounted on a conveyor belt? And how might data be used to help doctors predict the likelihood of diabetes and high blood pressure?
Many of the hands-on exercises I create are pulled from my conversations with Alteryx customers, whose size, industry, and data challenges vary widely. The exercises run the gamut in terms of industry, because there’s no telling where students will land when they finish the program. They could go work for Kaiser. Or a transportation logistics company for Amazon. I try to prepare them for all kinds of possibilities.
My students have access to a variety of tools in the course, including Alteryx Designer. Students can also learn the concepts and implementations using R or Python. Teaching and learning materials are now available through the SparkED learning materials on the Alteryx community.
Sharing practical uses cases from my daily customer interactions is one example of bringing real-world problems to the course. An executive once told me she doesn’t need more data scientists--she needs storytellers. Because her team can look at COVID data all night long, but if they can tell a story about what’s happening, where it’s happening, and why it’s happening right now, it’s much more useful. Telling stories with data tends to connect with my students. They say, ‘Hey, I can tell stories.’ A good place to find effective Alteryx use cases: https://community.alteryx.com/t5/Alteryx-Use-Cases/tkb-p/use-cases
With my students, I recommend that they tackle as many data projects as possible to gain experience, before interviewing with prospective employers. Some of these students are between jobs, many are international, and others are looking to acquire data skills for new career paths—but most will be in the job market before long.
The most important thing I tell them is to build a portfolio. Create info sheets on individual projects as a great way to get noticed, including a description of their role and approach. If they track everything they do in this program, that will validate their knowledge and skills, and will be a launchpad to their next job.
I like to think of myself as a bridge between Alteryx and UCI. I helped facilitate a hackathon, with other Alteryx sales engineers and managers helping as mentors. People are excited, and they love to help. At least one of my Alteryx colleagues has expressed interest in teaching data analytics, and I hope others will follow.