Managing and Mining Big Data for a Data-Driven World

Photo courtesy of Komal Vaish

“We are living in a data-driven world. There is so much data out there,” shared current Master of Supply Chain Management student, Komal Vaish. “The biggest challenge is being able to make sense of the data, present the data in a meaningful manner, and then telling a story.” Komal shared her experience and thoughts on what the course, Managing and Mining Big Data with Professor Hamed Mamani, taught her about working with big data sets.  

To prepare for a world that is more data-driven every day, students must learn how to analyze and use big data sets. “Our job as business managers would be to understand how large data sets work and what these data sets can tell us,” shared Komal. “As business managers, we would not be required to build complex models, but when data is presented to us we do need to make meaning of it.” This course aims to help students to think critically about data analysis, identify opportunities to apply data analytics in real business settings, and ultimately, to prepare them to lead an analytics team. 

Learning About Mining Big Data

The first phase of this course is about learning the data visualization tool, Tableau. Professor Hamed teaches students to use the various tools within Tableau to tell meaningful stories in dashboard form. “Though it’s a very simple tool to use in a sense, you really get powerful insights from it,” reflected Komal. “Professor Hamed showed us examples of how people have used this tool to show trends and tell stories about data. I also liked how he asked us to identify the information or insights we thought we could get with each example, which made it all the more interactive.”  

Students also dive into predictive analytics which involves using regression models to come up with insights and future predictions across industries such as tech, healthcare, banking, and entertainment. Though students are not meant to learn how to code directly from this class due to the accelerated format of the program, they do learn a software called Rattle, which sits atop of R, the actual coding software. Students use Rattle to mine data for their analysis with mere clicks. “That’s what is expected for us as business managers, not to learn how to code, but to be able to work through the data and analyze it,” explained Komal. “Not many of us were familiar with predictive analysis, so it was nice to see the different ways it could be used, get foundational examples of what regression means, and what the software does.”  

Putting Big Data to Use 

After learning to use the tools and scope out opportunities for data analysis in real business settings, students got to apply what they learned to group projects. “We got to make a visual of how NBA players should be drafted,” shared Komal. “We used a data set which had about 20 seasons of stats available as public records, and we did a logical regression model to predict a player’s performance and determine if they should be drafted.” Students completed a Yahoo Fantasy League using their prediction model to draft players for the online league. “When we didn’t have the model in place, our winning streak was quite low, but once we used the prediction model with our analysis, it increased considerably!” explained Komal. The group projects were a great culmination of the course because students got to experience first-hand how models have an effect on real-life work. 

“Overall, I was impressed with this course,” reflected Komal. “Professor Hamed was extremely passionate about teaching and gave us such a wide variety of examples on how to use these tools. Everything from his personal work to examples across industries brought this course to life.” 

To learn more about course at the Master of Supply Chain Management Program, visit our website.