ESTEEM Students Analyze Data on the Fly at SAP TechEd

Author: Notre Dame ESTEEM

Tuesday in Vegas was a busy day for the 6 ESTEEM Students chosen to represent the class at the SAP TechEd Conference,  Here, Paul Mahony discusses their participation at two events - MPH and Data Genius.

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Tuesday at SAP TechEd: the 6 students earned their SAP badges by helping out with some workshops – App Building space and IoT Lab. Fortunately we where saved when David Ryan, Director of MPH, spoke about the Notre Dame collaboration.

ESTEEM Students at MPH

David spoke about the work being done by MPH in Indiana and how they are collaborating with universities aiming at becoming the most transparent state government in the country. Notre Dame where the first of these collaborations, and through our work with statewide crash data, MPH hope to open this up to other classes, and other universities. ESTEEM student, Laura Shute, spoke personally about her experience with the project and some of the insights we found.

With the Notre Dame students now mini-celebrities among the conference organizers, we where also invited to participate at a Data Genius competition on Tuesday evening.

Made in a Free World have been working on a slavery awareness initiative. Their website, slaveryfootprint.org, asks the question “How many slaves work for you?”. The challenge given to us at Data Genius was to visualize real-world data, provided by the not-for-profit organization, to empower supply chain managers to target areas of highest risk regarding products sourced with forced or child labor.

Students Present Their Findings at Data Genius

Different teams took different approaches; ND examined how much money has been taken from source countries, the countries where the product comes from, compared to the countries who buy the products, and how unevenly the wealth is being shared. Other noteworthy mentions took the entire supply chain and looked at areas of high risk, the winners in the end visualized the entire data set where someone could find any info they wanted in a beautiful picture.

In conclusions, Tuesday was a mix of work and more hand on experience using predictive analytics to solve real world problems.