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Importance of data analytics leads students to concentration

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Thursday, February 6, 2020

With the rapid rise of data in our various environments, data analytics becomes crucial to learn and study. Personally, I see most of the students around me picking up the data analytics concentration alongside their business majors in Krannert. With new buzzwords like big data, data mining, machine learning and more, it is no surprise that I am surrounded by people interested in data analytics. Here is more information on a few of the courses that I took for my data analytics concentration:

1. ECON 360 – Econometrics

Econometrics applies quantitative analysis and models onto economics to test hypotheses and forecast the future from historical data. It is fairly heavy in data and statistics. It was interesting for me because I was able to learn new statistical techniques and theories to apply onto existing economic problems in the real world. For example, my major assignment in class was to write a research paper on any topic in econometrics. I used statistical techniques learned in class to find the relationship between amount of revenue and number of employees in Fortune 500 companies. This was an opportunity to look into a real-world issue I had always been wondering about. In the process, I gained a new technical skill by learning how to use STATA, a type of statistical software. This class is known to be highly challenging, which makes sense because there is high emphasis placed on statistics, math, and is extremely data-focused. Nonetheless, I enjoyed the challenge and would recommend the class to students who are willing to work hard to gain more skills in data analysis and statistics.

2. MGMT 472 – Advanced Spreadsheet Modeling and Simulation

All Krannert students are required to take CS 235, which is a basic introduction to Microsoft Excel. This class allows students to further delve into Microsoft Excel to learn the application of spreadsheet modeling in business, such as analyzing risk or forecasting stock prices and pricing options. I am currently taking this class, and have enjoyed the deeper review of basic concepts learned in CS 235. Although I am a bit afraid to start learning about simulations with risk analysis in Excel, I am also excited for this challenge and opportunity to learn a new skill. As a finance major, I believe this class will be truly beneficial for me because I will soon be able to apply more technical skill to financial issues.

3. MGMT 473 – Data Mining

This class is teaching me the importance of applying meaning to data. Without analysis and mining, the significance of data is minimal. This class teaches students various data mining methods such as regressions, decision trees, memory-based reasoning and more.  So far, we have mainly been learning how to use SAS Enterprise Miner to organize data sets. It has been thoroughly interesting for me to learn about the components of and universal need for data mining. Comparing the types of data, in addition to learning how to organize and summarize it, has taught me how to apply my statistics and financial skills onto data mining. I am super excited to learn even more about how to evaluate the quality of data mining or use direct statistical models, which we will be completing later in the semester.

Data analytics is one of the most relevant topics in our generation. I was inspired to pick up a concentration in data analytics after my past internship at a technology company last summer, and I am deeply grateful that I was able to fit the classes in my schedule. I would encourage students, if looking into a more technical addition to their degree, to look into data analytics or statistics. Personally, I have gained so many more technical skills and see that the challenging work has been worth it!


Anna Pi is a junior from Seattle studying Finance with a Concentration in Data Analytics at Krannert. She is a study abroad ambassador, after studying at HKUST her sophomore year.
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