Stream: Mainframe Skills & Learning
Time: 11:15 - 12:00
Mainframe systems power critical operations across industries, generating vast amounts of data every second. But raw data alone isn’t enough, it needs to be translated into insights that people can understand and act on. That’s where data visualization comes in. This session explores how tools like Python and Tableau can be used to transform complex, enterprise-level datasets into clear, interactive dashboards. From system metrics to weather patterns, the focus is on turning technical information into visual stories that reveal trends, anomalies, and opportunities , even for non-technical audiences. Attendees will gain practical ideas on structuring data pipelines, designing effective visuals, and integrating modern analytics with traditional systems. Whether working in IT, analytics, or decision-making roles, participants will leave with new strategies for making mainframe data more meaningful, usable, and impactful.
There is currently no attachment for Visualizing the Invisible: Bringing Mainframe Data to Life with Tableau
I am a postgraduate student in Data Science and Analytics at the University of Hertfordshire, with a strong passion for bridging traditional enterprise systems and modern data technologies. I have hands-on experience in Python, R, and Tableau, and have developed projects in data visualization, machine learning, and analytics using real-world datasets, including weather prediction, spam detection, and credit card fraud analysis.
As an IBM Z Student Ambassador and dedicated mainframe enthusiast, I actively explore complex enterprise systems, using storytelling and visual insights to make them accessible. I have participated in multiple tech events and workshops, including the IBM Z Xplore learning platform, hackathons at the University of Hertfordshire, and the WAVEZ virtual conference, where I collaborated with peers to solve real-world challenges.
Beyond academics, I serve as a student representative for my department, mentoring peers and supporting collaborative projects. I am committed to sharing knowledge, empowering emerging professionals, and inspiring others to embrace data science and enterprise computing.
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