Demand for data analysts isn’t slowing down anytime soon. Hiring of data analysts and operations analysts is projected to grow 25 percent through 2030, according to the Bureau of Labor Statistics. Analysts play a vital role in banking, insurance, healthcare, and industries that rely on data to forecast growth and interpret trends.

Based in Kansas City, Dr. Alex Francisco knows the importance of data analysis. As director of the Office of Population Health Science and Statistics in Kansas City, he uses data analytics to research, understand, and improve the health of populations, particularly during the COVID-19 pandemic. In the upcoming virtual workshop Introduction to Data Analytics (March 23 and 26), participants will learn from Dr. Francisco’s real-world experience and expertise.

Below, Dr. Francisco shares insight on the value of data analysis, and how his upcoming course builds a strong foundation to explore the field of data science.

What is the value of data analytics as a tool for strategic decision-making?

Data analytics and interpretation are vital to ensuring the success of nearly any organization in the current environment. Strategic decision-making without data analytics is really just guessing. If you don’t use data to drive your decisions, then what are you actually using?

How do you use data science and analytics as a population health scientist?

A main part of my job currently is using data science and analytics to understand COVID-19 – but not just who currently has it. Using data science and some computational models, I was able to predict the summer 2021 surge, caused by the delta variant, a full month before the peak in early August. My final predictive model was accurate within 5 percent of the peak, and was generated on July 6^th when we had 349 cases over 7 days. The model suggested we would have 1550 cases the week ending August 7^th. We ended up having 1,630. This prompted the city to reinstate a mask mandate.

“Strategic decision-making without data analytics is really just guessing. If you don’t use data to drive your decisions, then what are you actually using?”

Is there a common misperception or misunderstanding of what data analytics is?

Data analytics doesn’t produce answers. Only the data scientist or analyst can do that. Similarly, data analytics as a tool is only going to be as useful as the data that you analyze. You can’t use data science to understand your data. Good data science combines the acts of gathering data, organizing, analyzing, and then interpreting data as accurately as possible.

Will you share real-world examples of data analysis in your workshop?

I will illustrate how COVID deaths are linked to case rates in age groups that have relatively few deaths, illustrating the COVID-19 is a community problem and not an individual one.

What can participants gain from the workshop as they prepare for the data analytics industry?

Workshops like these really highlight the most important components of the data analytics industry right now. The tools to conduct data analysis are getting easier and easier to use, but the ability to discern good data science from poor data science is not keeping up. Taking courses like this one can ensure that as you progress in your data analytics career you start with the best possible foundation to build from.

Introduction to Data Analytics is one of seven courses in the UMKC Data Analytics Workshop Series. The Series consists of seven instructor-moderated interactive courses. Begin with one course or attend a series of three workshops to earn a non-degree certificate from UMKC TalentLink.