I’ve heard a lot of talk in the corporate world about analytics, but I’m not sure people always understand how important it is. The amount of data produced daily is exponentially increasing and expected to grow 30 times larger in the next decade (IDC, Digital Universe Study, April 2010). Analytics is going to be the key to data discovery, encompassing the talent to interpret and produce value from the data.
What exactly is analytics? At a high level, I’d say it’s the combination of applied statistics, programming and business skill sets.
Despite the high demand for analytical talent, the MSA program at NCSU is the only graduate degree in analytics in the country, and it’s only three years old. Completing the program takes 10 months, and it simulates the real world with its full-day schedule.
I am in my fifth week in the program and have already been exposed to so much amazing technology. We have learned SAS, DataFlux, GIS mapping software and, last but not least, JMP software. The MSA program also incorporates communication training in the technology courses. That’s because it’s important to not only be able to analyze your data but also to convey your results effectively.
So far I am really enjoying the program and am looking forward to learning more about marketing analysis, which is the area I would like to work in when I graduate. The program also focuses heavily on group work, and I’ve learned a lot from other students in the program who all come from different backgrounds and have varying experience levels.
The more I delve into analytics in the classroom and apply it to real-world situations, the more ways I find to use JMP. Before starting the MSA program, I enjoyed learning JMP as an intern, taking a class at SAS for using JMP for ANOVA and regression, along with watching webinars and learning from technical presentations. This past spring, I used the predictive modeling platform in JMP Genomics to analyze our marketing strategies and predict buying patterns. I feel like I learn a new trick every time I use JMP.
Recently, I have been using JMP in my summer group project for the MSA program. The ease of use and the way JMP displays the data to allow for interactive changes let me quickly try different things to see what works and what doesn’t. I really loved using JMP to clean my data and found the summary tool under the tables tab to be my best friend. JMP allows for simple column recoding, easy sorting and data validation with range checking in place to find weird data. I also used the distribution option under analysis a lot for checking my data and getting to know it better, as well as for testing assumptions with the probability plot and variance tests.
Graphics is an area I am really interested in and one in which JMP excels. Graph Builder is my favorite tool. It’s an easy and cool way to plot variables quickly and determine which relationships to test. JMP has many other graphing options, some of which are outputted automatically depending on the procedure you are doing.
Overall, I find JMP to be a great tool for discovering trends in data, analyzing results and displaying those relationships graphically for better understanding. Every day, I continue to learn the many applications of JMP in the analytics realm, especially since I have been in the MSA program. I appreciate that JMP places importance on analysis and discovery with its ease of use and functionality. Our reliance on technology is a strong dependent relationship, and using tools to provide more efficiency in the way we handle data will only become more important as we go on. After all, “the sexy job in the next 10 years will be statisticians,” according to Hal Varian, Chief Economist at Google.
If you'd like to learn more about using JMP in your classes -- whether you are a professor or a student -- you could sign up for an upcoming live webcast by the JMP Academic team on "JMP Basics for Professors and Students" or "Teaching Statistical Concepts with JMP." You might also want to check out the on-demand JMP Academic webcasts.