The following is a Q&A with Ben Olsen, our instructor for the Business Analytics program. Ben is Sr. Program Manager in Data and Analytics at Microsoft and CEO of Analytics Guild, a company that guides data professionals toward mastery in their field. He holds a B.A. in Philosophy from Seattle Pacific University and recently served as Instructor in Data Visualization at the University of Washington.

Let's start with the basics: why did you choose a career in data analytics?

Computers were always a part of my family, in my earliest memories, because my father was (and still is) a tech consultant. The funny thing is that I never knew what he actually did at work until I got a job in his consulting firm. I was in graduate school for philosophy at the time and chose to leave the program; I had decided that I’d rather get a “real” job and marry my girlfriend (now wife), so I dove into what was called “Business Intelligence”—more commonly known today as Analytics.

My undergraduate training at SPU, also in philosophy, honed my ability to ask questions of complexity and depth, and to find my way through them to answers that are (hopefully) logical and true. The driving force is curiosity, a deep desire to know answers to fundamental questions about knowledge, reality, truth, and what we should do—and these are inherently present in data work, albeit with a strong math/science/business lens. The technical side of analytics is assisted by logic; a lot of data work is a combination of predicate logic with set theory (think: Venn diagrams, and you’ve got 90% of set theory).

Through a series of job opportunities that stretched me beyond my work experience, I’ve accomplished many things in the field of analytics, and I couldn’t have done it without the certificate program I took about four years ago. That certificate landed me a job that opened so many doors. In fact, I came back and taught a course in the same program for two years, so I’m a big believer in what these shorter, more intense, focused programs can offer students in terms of a career accelerator, validator, and more.

 

Your background includes study at Stanford University and University of Washington, as well as teaching at UW—how do these things translate into your work?

My studies at Stanford for Decision Science continue to be important because that program taught me the science of good decision-making. In business, making good decisions is critical for the success of the company. Our micro-decisions combine together to form our culture and society. I use the principles I learned there every day.

Similarly, my experience getting a certificate in Business Intelligence was key to jumpstarting my career in analytics, and it inspired me to found this program. In my work, teaching and mentoring is like being a coach for fellow employees, regardless of rank, and negotiating tough questions and personal territory—goals, egos, skills—in relation to what needs to be accomplished.

My most recent education-related work was with Microsoft as the founder of Analytics Guild, an analytics education and consulting company, where I created a MOOC (massive open online course) that has been taken by thousands of students in over 120 countries. I'm proud of this work, which is a distillation of much of my thought on the business side of analytics. The Business Analytics certificate at SPU will be an extension of that because the techniques themselves will be expanded upon and demonstrated, and we will explore more territory as it relates to data science, big data, and the deeper questions about data that businesses are only now starting to realize are important to the future of their competitiveness as well as their responsibility to the world at large.

 

What do you wish non-initiated folks knew about analytics?

Analytics and the business of data is so much more about clear communication and soft skills than it is about technical wizardry, and I think most programs out there sell this short. While programming concepts and query optimization are important, the truth is that these skills are getting commoditized faster than people can learn them. Great analytics professionals internalize the fundamental “truths” of our discipline, learn a number of core skills and techniques along the way, and then jump into the stream (or rather the raging river) of the analytics economy. Chances are that each one of your analytics jobs will require a new tech stack, or a new way of implementing or problem solving such that you never know enough, so adaptability is key. Our program at SPU is designed to give you enough to be dangerous in so many interesting and fantastic data situations. We can’t wait to share.

 

What has been the proudest moment of your career so far?

I’m going to have to give you two kinds of moments, and that’s because I view them both as doing what I call “creating economic opportunity.” The first is that I’ve had the great pleasure of hiring many of my friends or finding them jobs that bring their careers that much closer to reality. For example, through my first company I made the decision to use some company funds to help one of my friends learn computer science while he was doing his Master’s degree in philosophy, under the condition that when he got out, he’d give my company a try. Years later, he’s a successful data scientist and I couldn’t be prouder of that—the fact that I could be a part of that journey in finding what he loves to do and that he can make good money doing it.

The other side of the coin is when I use data to make a real impact in a business that I’m working with. For example, I consulted at a large telecom company, and in one big data project (which I was directly responsible for) we found a way to work through the ambiguities of logic and constraints to save the company many millions of dollars. Solving those types of problems makes me so proud. But now that I think about it, I’m still more proud of helping friends along the way.

 

You're a working professional, rather than a full-time professor. Why do you teach on the side?

The old adage that "those who can’t do, teach" is a terribly anachronistic and pessimistic perspective on what I think is one of the most rewarding things about being in the analytics profession right now. Analytics is so practical, yet also theoretical, that if you want to succeed in it you need a guide and mentor to help you separate the wheat from the chaff of the discipline. Those who have done so for me have saved me a lot of heartache. I believe that I can and should do both as a data practitioner and as a coach and mentor.

 

One thing I think we're all searching for is a job that allows us to exercise our ideals to some degree; in other words, there's an ethical dimension to choosing work if you have the privilege to choose it. How has your work meshed with your sense of doing good in the world?

Data work gives businesses (and the world) a chance to have another lens on reality: one of facts, arranged and displayed and analyzed to such a degree that they distribute answers about what happened, what is, and what may be. That is so powerful! How could it not relate to the things we most care about? Stories we hear in the news and articles we read in our favorite magazines are chock full of these data points, but how they’re derived is no longer proprietary or secret. Anyone with enough curiosity can now learn to leverage data as yet another addition to the larger story about our lives.

Analytics is so powerful that it ought to have its own version of the hippocratic oath: a view toward assisting businesses and society at large, using proper methodologies and the kind of thinking that used to be more associated with humanities. Holistic perspectives.

 

What do you like doing when you're not working?

Making up stories with my two-year-old daughter is my most important hobby, but besides that I like to dream up new businesses, do yoga, cook, play a tabletop game or two, and occasionally turn off all the data and find a mountain to climb with friends.

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