On Friday, February 22nd, OPIM Innovate hosted its Splunk Analytics Workshop. There, Professor Ryan O’Connor, UConn adjunct and Splunk Senior Advisory Engineer, explained to students the origin of Splunk and its uses. Other than Splunk’s three premium solutions: Splunk Information Technology Service Intelligence, Splunk Enterprise Security, and Splunk User Behavior Analytics, attendees also learned of the knowledgeable and supportive community behind the service. From dedicated end-users to passionate Splunk professionals, this community develops intuitive applications utilizing Splunk while also answering each other’s questions. Splunk, therefore, is a user-oriented platform which does everything in its power to help companies and individuals succeed with its data monitoring and visualization software.

During the workshop, O’Connor introduced students to time series data, which is how Splunk got its initial patent. In short, time series data is data that has been indexed on a time scale, either to organize the data or to derive conclusions from certain time intervals. For example, credit card companies use time series data in order to deduce whether or not purchases are being made by the authentic cardholder. In Splunk, machine data is categorized and searchable by date and uses time to sort out feasible and non-feasible data. If a purchase is made in one store in Connecticut, and then another store in Vermont 30 minutes later, chances are the card in question has been compromised.

Splunk is a very flexible service that allows users to integrate data from other software such as SQL Developer, a database client. “Databases are everywhere and important,” O’Connor explained to students, “but, some database clients don’t visualize data well. They just store it, keep its structure, and that’s it.” That is why O’Connor developed an application, called DB Connect, that can grab database information, make a copy of the data inside of Splunk, and then visualize it. “It can make pie charts, line charts, or whatever the case may be,” said O’Connor. “Splunk isn’t designed to replace any one of these [database clients], but instead to aggregate data from them.” Splunk can also capture real-time web data, such as the number of times a server is pinged by a computer or the number of times it is successfully infiltrated.

For those interested in Splunk, Splunk Fundamentals I and II are free for UConn students. The ability to use Splunk Analytics is a very marketable skill, especially for those interested in entering the world of information technology. Also, on March 8th, OPIM Innovate will also be hosting Splunk Day, where students can network with Splunk professionals. Don’t let these important networking opportunities pass you by! Get started with Splunk, today!

 

 

 

 

On Friday, February 22nd, OPIM Innovate co-hosted the Totally Teched Out Late Night Event in collaboration with UConn Late Night. In the Student Union, Room 104, a number of students from different academic backgrounds interacted with emerging technologies such as virtual reality headsets and leading software like Splunk Enterprise and HP Reveal. While many students walked in without prior knowledge of OPIM Innovate, they left with a piqued interest regarding what the initiative has to offer.

During the event, the Innovate Room was set up so that students could get a mini demo of all the technologies up for use. After signing in, students were first introduced to HP Reveal, an augmented reality application that superimposes digital images and video onto the real world. Then, they were introduced to Splunk Shake!, a Splunk Enterprise demo developed by Innovate’s Nathan Hom (’19 Management and Engineering for Manufacturing) which captures real-time data generated from shaking your phone. From there, students branched off into virtual reality demos or drone flying, either utilizing virtual reality headsets like Google Cardboard, the HTC Vive, and the Lenovo Mirage Solo, or flying drones of different shapes and sizes. The room was filled with rotor blade buzzing, laughter, and sounds of awe triggered by virtual reality immersion.

For some students, the Innovate Room at the Totally Teched Out Late Night Event was the first time they had ever encountered some emerging technologies or software. Xiaofeng Gong (’20 Mathematics and Economics), for example, had never heard of Splunk Enterprise before being introduced to the software by Nathan Hom. “After the Shake! demo, Nathan enthusiastically gave me a brief introduction to Splunk Enterprise since he saw that I was so interested. His enthusiasm and the software’s ability to monitor machine learning and capture real-time data really got me interested in data science. Now that I know that Splunk Fundamentals is free for UConn students, I will definitely check it out. Here was the right place for me, tonight!” Other students, such as Syed Hussain (’19 Communications), had a similar first-time experience with virtual reality, specifically with Google Cardboard. “Overall, I found the [Google Cardboard] experience super interesting coming from a gaming perspective,” Hussain said. “I always had an idea of how I would experience it, but I wasn’t expecting the images to be as crisp as they were.”

For the students running the Innovate Room, the hustle and bustle was worth every minute of getting to see interest emerge in another student’s face. Hannah Bonitz (’19 Management Information Systems), for example, felt accomplished knowing that she was helping bridge the gap between Innovate and the rest of the UConn student body. “I’m happy about the turnout,” Bonitz said, “and its very exciting to see that people are willing to come out on a Friday night to learn more about technology.”

 

Thank you to everyone who visited the Innovate Room on Friday! We hope to attend more events like the Totally Teched Out Late Night Event in the future!

On Friday, February 15th, OPIM Innovate held its Introduction to Artificial Intelligence (A.I.) Workshop from 1:00 PM to 3:00 PM in the Gladstein Lab, BUSN 309. Led by Stephen Fitzgerald, an adjunct professor in the Operations and Information Management (OPIM) Department, the workshop covered various aspects of artificial intelligence, including neural networks and evolutionary computing. As Professor Fitzgerald explained during the workshop, “A lot of intelligence as far as artificial intelligence goes is modeled after human intelligence–the way that humans make decisions, and the way that they think about things.” However, throughout the workshop, students learned that these models are more mathematical than contextual. In other words, machines do not have the capacity to understand complex ideas, but this does not always mean that they cannot perform tasks better.

After a brief overview of the different areas and categories of artificial intelligence, students were paired up for an introductory activity. During this activity, one student from each group was told to keep their head down while the other student was shown a picture on the projector screen. Once the picture was covered back up, the students who had seen the image were told to explain to their partners how to draw it without context (for example, you could not say “cat” or “falling”). Instead, they could only explain things mathematically in angles, degrees, and shapes, mimicking the understanding of a computer. Both partners had an opportunity to draw and give directions, and many students were scratching their heads in the process. The photo on the left is of the drawings I and junior finance major Christopher Narkon were able to conjure up. Given the two tails I drew on what is obviously a cat, thinking like a machine can make understanding the world very difficult.

As the workshop continued, one student brought up a good point that resonated with Professor Fitzgerald: due to a machine’s immense computing power and inability to comprehend distracting stimuli, it oftentimes has the upper hand regarding task accuracy. Machines can learn from mistakes, become as precise as possible with the steps they choose for task completion, and create preemptive and accurate decision maps. As such, projects like Deep Blue, Alpha Go, and AlphaStar have been able to beat the world’s best strategy-game players in games like chess, Go, and Starcraft.

After the workshop, students were left baffled with how immense the world of artificial intelligence has become. One student, junior MIS major James Mercaldo, stated, “I didn’t know there were a lot of hidden stages in machine learning. I always thought it was a fixed, input/output thing.” Yunqian Zuo (’22), a management and engineering for manufacturing major, added, “I didn’t know there were so many different branches [in artificial intelligence].”

For students who want to learn more about artificial intelligence, OPIM Innovate has tech kits that can be individually completed at your own pace.

Thank you to everyone who came to the Introduction to A.I. workshop. We hope you had a wonderful time!