On Thursday, November 7th, Hanover Insurance and OPIM Innovate co-sponsored a Data Visualization workshop. Run by Olivia Rossetti (Management ‘15), Senior Data Integrity Specialist at Travelers and UConn alum, students were introduced to data visualization fundamentals and the Tableau software. 

Rossetti’s framework for introducing students to data visualization began with a general overview of the topic. After defining the purposes of both data and visualization separately, she presented students with the three following definitions: 

In order to visualize data, students had to understand the four key components of data visualization: visual cues, the coordinate system, scale, and context. Whereas visual cues use elements such as shape, size, and color to portray certain values, the coordinate system, scale, and context of a visualization assign additional meaning to those values. Take a bar chart, for example. The length of each bar indicates a numeric value, and color can be used to distinguish between categories. Meanwhile, the chart’s coordinate system can help users determine specific values, and any added labeling, annotations, and titles can help users identify the context of the data being shown. 

Of course, with any chart or visualization, there is always an intended purpose and audience in mind. For data visualization, artists can compare between data points, display parts of a whole, help users identify relationships, or even show the distribution of a dataset. What to do, however, depends on the needs of the audience, including what they may not know and what they could potentially get out of a certain visualization. For example, if someone wants to know the types of users that log onto a website, it wouldn’t be productive to create a visualization showing a distribution of total logins throughout the week. 

After Rossetti walked attendees through the foundational knowledge needed to understand data visualization, she proceeded with the hands-on component of the workshop–working with Tableau. Everyone gained access to the software through the School of Business virtual machine, and exercises were completed in real-time. One of the many visualizations made consisted of using a provided superstore dataset to display sales by product category, customer segment, and market:

Another, more intuitive visualization, consisted of portraying global sales and profit. Size was used to indicate the degree of success for sales. Color was used to indicate profit at a gain or loss:

After the workshop, I approached Rossetti regarding her motivations for returning to UConn, not only as a guest lecturer, but also as an adjunct faculty member. Outside of this Data Visualization workshop, she teaches OPIM 3804: Data Visualization, open to all Management Information Systems (MIS) students and Data Analytics minors. “When I was a student at UConn,” she said. “I wasn’t sure in which direction I wanted to go in. I started as a Management major, finished all of my requirements, and then heard about the certificate in OPIM [the Data Analytics minor]. That led me into the world of analytics, a path I never imagined. Because I had that opportunity as a student, I was exposed to classes that were taught by adjunct faculty. There, I was able to see what they were doing in the real world, and what tools they were using. I knew from the moment I met one of my teachers [adjunct Marshall Dougherty], that I wanted to provide the same experience down the road–I wanted to make an impact.”

We thank Olivia for her contribution to the Hanover Challenge and to the MIS curriculum. We also extend a warm thank you to everyone who attended the Data Visualization workshop!

On Thursday, October 31st, Hanover Insurance and OPIM Innovate co-sponsored a Predictive Analytics workshop. Run by alumni and Travelers Data Integrity Specialist Aleya Hafez (Mathematics & Statistics‘18), students were introduced to different data modeling approaches. 

Hafez’s lecture followed the usual data modeling framework–cleaning data with hypotheses in mind, splitting data, and finally creating predictive models. This, of course, came with the need to explain what each segment entailed, information she generously opened with. In explaining the data cleaning process, she informed students of potential outliers, duplicate records, data input errors, or any other abnormal or extraneous data that may skew test results. With regard to splitting the data, she taught students the difference between a training dataset and a test (or validation) dataset. In brief, training datasets and test datasets are samples taken from the whole; training datasets are used to build initial models, whereas test datasets are there to verify results. As for creating models, Hafez specified the process to further increase understanding.

To provide students with a conceptual guide of data modeling, Hafez broke down the process into the following steps:

From these steps, she then explained separate modeling types, such as linear regression, logistic regression, and decision trees. Whereas linear regression predicts specific numeric values, logistic regression and decision trees predict the probability of something being true or not. For example, a model using logistic regression will be able to predict whether an email is spam or not. A decision tree, on the other hand, brings these probabilities into finer and finer levels depending on the number of nodes, or categories, added (see below):

Decision trees may also be used to assess model outcomes against actual data. This helps data scientists select the best models to use. 

To end the lecture, Hafez used the concepts she described to create predictive models in R. This gave students the chance to see data modeling in action, and provided them with enough of a preview to ask clarifying questions. 

When Hafez was asked why she volunteered her time to share her knowledge on predictive analytics with UConn students, she said the following: “I’ve always enjoyed helping other people, and it excites me to know that someone other than me is interested in statistics. It’s great to see that the UConn School of Business is putting more of an emphasis on predictive analytics, so I’m happy to give my take!”

We thank Hafez for her time and everyone who attended the Predictive Analytics workshop!

 

On Monday, October 21st, UConn held its annual Experience Innovation Expo in the Student Union Ballroom. There, OPIM Innovate Lab Specialists Eli Udler (English & CS ’20) and Vaughn Nangle (Physics ’20) introduced students to emerging technologies and agricultural solutions, such as virtual reality (VR) headsets and hydroponics. The VR headsets, especially, were a hit due to the photorealistic graphics of the Oculus Go. Students were immersed in titles such as Jurrasic World VRSE, where they could watch dinosaurs thrive in 3D.

Udler, a wearable technology expert, also networked with the Puppet Arts department during the Innovation Expo. Having experienced working on wearable technology projects before, he believes UConn Puppetry can benefit from technology integrations. This may vary from projects including the Mindwave, a device that can read brain patterns, to Adafruit sensors that can detect sound and movement. “I’m excited to help introduce Innovate to different UConn departments,” said Udler. “Working with puppets will be a fun challenge.”

Both lab specialists had a great time demoing the latest and greatest technologies to those curious enough to stop by. “It was cool to see people so interested in what we do,” Nangle said. “Now I just wonder what they’ll do with our resources.”

We thank everyone who visited our booth during the Experience Innovation Expo and to the Werth Institute for putting this event together!

On Wednesday, October 16th, OPIM Innovate was invited to share its technologies at the annual Research Connections event. There, at Werth Tower, the initiative gained traction by making itself known to early-career undergraduates who had not yet been exposed to the lab. The purpose of Research Connections is to help UConn students find potential research opportunities and give exposure to projects that usually span across campus. “We thought it would be a great idea to showcase,” said Innovate Lab Manager Robert McClardy Jr. (CS ’20). “We want to help students explore their ideas and we have the resources to do it.”

During the Research Connections event, McClardy and other OPIM Innovate lab specialists networked with interested attendees. Many students from the College of Liberal Arts and Sciences and the School of Engineering stopped by the booth. The exchange proved to both parties how universal the initiative can be–everyone has the potential to innovate. “We connected with quite a few students and hopefully they’ll come check us out sometime,” said McClardy. These students interacted with the technology and end-products on display–namely virtual reality headsets, drones, and 3D prints. “To encourage brainstorming, we told them about some of the projects we’ve done in the past,” added the lab manager. “Everything starts with an idea.”

We thank everyone who stopped by our booth at the Research Connections event! For more information on OPIM Innovate, stop by our website!

 

 

 

On Friday, October 4th, the Operations and Information Management department hosted its annual MIS Case Competition. Focused on exposing UConn students to real business problems, the competition asked participants to work together in order to create and defend potential solutions. This year, the case surrounded Connecticut Bank, a fictional financial institution attempting to enhance its security measures to further bypass the consequences of identity fraud. Biometric technology was the main focal point across teams–from fingerprint scanners on credit cards to voice authentication for mobile banking applications and call centers.

Throughout the day, each team expressed their business solutions to a panel of judges in the form of a 15-minute presentation. Each presentation was followed with 10 minutes of Q&A, where judges tested teams on their ability to think on their feet. “We asked [students] difficult questions, not because we wanted to give [them] a hard time, but so we could expose [them] to [an additional challenge],” said judge Craig Calvert. The best teams were those who evidently rehearsed their slides and supported each others’ answers when appropriate.

During the Awards Dinner, which followed the competition, students were thanked for their participation. While not all teams walked away with a cash prize (the top award being $500 per person), they each had the courage to tackle the challenge. All teams were given one week to research and design their slides on a topic that is still emerging and, to an extent, theoretical. They had to crunch numbers, scale technology, and generally think for both the bank and the consumer.

Not all winning teams were well acquainted with case competitions. In fact, the first-place team was composed of two first-time competitors: Julia Moody (MIS ’21) and Dean Perkins (Management ’20). Named The Buzzbees, both used their trust in each other and honest feedback to pave their way to victory. “I gained confidence as we went through the process of practicing,” said Julia. “I also learned that having team members with different perspectives can really make a difference in a project.” After Dean and Julia were awarded their first-place certificates, Dean had this to add regarding his experience: “I feel a little bit surprised, but I knew we put the effort in. Our greatest ally was planning and…practicing. We picked on each other and looked for areas of improvement. By the time we got to [the competition], we were relatively calm.” Dean and Julia had a third member of their team who had to drop out due to health reasons, further emphasizing the strength of proactive teamwork.

We would like to extend a warm thank you to those faculty members who volunteered their time to help make the MIS Case Competition a reality.

Interested in the MIS Case Competition? Stay tuned for the next round coming up in Fall 2020.