Do you use spell check or autocomplete when you write? Have you ever gotten a recommendation for a TV show, movie, or product that turned out to be just what you wanted?
These helpful tools are made possible by analyzing past data to predict what should come next. It makes sense that if you enjoyed action movies in the past, you will probably like one tonight, right?
Generally, we refer to data analysis to support better decision-making as “data analytics.” That can involve better decisions on what comes next when you’re writing, which movie you might like to watch tonight, or many other decisions you make regularly. When we consider how data analytics works within the business world, we mean that data is used to discover ways to improve a business. Data analytics can assist in business decisions such as how best to order inventory, set prices, or identify our best customers.
One way to think of data analytics is as a range of options.
On one end, we have data science, the most technical branch of analytics. It typically requires advanced training in statistics and computer science, often in the form of a doctoral degree, and focuses on the theory and tools of analytics. At the other end, we have business people who want to make better decisions. They need some knowledge of analytical tools and techniques, but the business context is more important. It isn’t the tool but how it is used that really matters to this person. This end of the range is “applied data analytics.”
What gets the most attention in the media? Since October 2012, when the Harvard Business Review called “data scientist” the sexiest job of the 21st century, data science has been getting all the ink. But that overlooks an important issue: only a small fraction of companies have the resources they can dedicate to a proper data science effort.
Most small- to medium-sized companies (and a lot of big ones, too) need to find ways to get value from data inside accounting, finance, marketing, logistics, and other operational departments. The solution lies at the applied end of the data analytics range.
A knowledgeable analyst can discover hidden insights in data in many ways. Some are as simple as organizing and visualizing data. For example, say an air conditioning manufacturer is having problems with units arriving in one part of the country with cracked tubing. When looking at the shipping data for the damaged units, the manufacturer discovers that poor road conditions are causing huge jolts to the trucks carrying them, which leads to the cracks. With this discovery, the air conditioning manufacturer is able to upgrade the suspension systems used on those routes, and the expensive problem can be solved.
Because applied data analytics tools are a common solution to business problems, a career in data analysis is a wise choice.
At the UCA College of Business, we have undergraduate and graduate programs that teach the concepts and skills to prepare students to use applied data analytics. Students at the undergraduate level can get the same solid business foundation as our other programs while learning about analytical tools and techniques. Our technical certificate serves as a standalone credential for anyone who wants a foundation in data analytics to boost their career. The graduate-level programs are hands-on programs intended for working professionals and others who want to expand their skill set or are looking for a career change. The Graduate Certificate in Data Analytics is an introduction to applied data analytics that can be completed alone or as part of the MAcc or MBA program. Our Master of Science in Applied Data Analytics takes the student deeper into analytics while keeping one foot firmly planted in the business world.
Building complex statistical models from scratch might be interesting, but it doesn’t provide value for most companies. If you are more interested in solving business puzzles than in creating fancy models, check out our programs. Or, if you are running a company with a huge amount of data and aren’t sure how to get value from it, keep your eyes open for one of our graduates!
About the Author
Mike Ellis
Dr. Michael Ellis is an Associate Professor of Computer Information Systems and Analytics (CISA) at the University of Central Arkansas (UCA) College of Business, where he has served since August 2014. He earned a Ph.D. in Information Systems from the University of Kansas; he also holds an MS in Management Information Systems from the University of Houston and an MS in Finance from Texas A&M University. Ellis teaches both undergraduate and graduate students and has numerous published scholarly works.