Big Data EdCon 2019


The Global Analytics Competition (GAC) is a worldwide inter-varsity competition aimed at generating innovative analytics solutions. The GAC competition also aims to raise awareness around environmental issues and sustainability.

See videos from the 2019 competition.



State University of New York at Buffalo - FIRST PLACE
“Waste Management Report-Erase the Waste”
Nidhishant Dixit, Sithara K, Roshan Jain
Dr. Ram Ramesh 

Dalhousie University - SECOND PLACE
“Natural Water Resources: G-7 versus Next 11”
Kyle Jacobson, Anthony Saikali, Justin Zuccon
Dr. Kyung Lee

University of Connecticut - THIRD PLACE
“The Catastrophic Effects of Global Warming-The Forces at Play”
Barbara Lucas Johnson, Carl Johnson, Prasanthi Lingamallu
Dr. Girish Punj

University of Maryland University College
“Effects of Pesticide Usage, Cell Phone Towers on Bee Colonies in the United States”
Megan Brumbaugh, Rajesh Kumar Gnanasekaran, Yelena Bytenskaya
Dr. Steve Knode

University of Maryland University College
“Tracing the Sources of Green House Gas Emissions, Globally and in our Backyard”
David Silberman, Ellen Tappin, Isaac Asiedu
Dr. Steve Knode 

Deakin University
“Exploration of relationship between air pollution and population”
Branu Jeyavarman, Christine Joyce Carlos, Virasak Sokun
Dr. William Yeoh

Deakin University
“A report on CO2 analytics for Fossil fuel energy, Renewable energy, and Nuclear energy from 2010 to 2015”
Haoli Wong, Qingbao Liao, Adrian Inn Wai Ng
Dr. William Yeoh

Deakin University
“Air pollution and health impacts: Environmental Analytics”
Ruchika Rokade, Tejas Patil, Abhishek Gharge
Dr. William Yeoh

Fordham University
“Analysis Association between Economic Growth and CO2 Emission”
Gege Tao, Yuwen Wu, Haofeng Huang
Dr. Pasumarti Kamesam

Fordham University
“Exploring the Environmental Benefits of Shared Transportation Methods in the U.S.”
Boyin Zhu, Bingdi Chunyu, Yao Jing
Dr. Wullianallur Raghupathi


Teams are comprised of of three students at the undergraduate or graduate level and an academic supervisor. Each team is required to have an academic supervisor. Submissions are welcome from teams at the undergraduate or graduate (e.g. US masters programs)/postgraduate (e.g. master programs in UK or Australia) level. Participation of students from analytics, data science, MBA, IT, information systems disciplines is highly desired.


The competition topic will be on environmental issues. Your main task is to apply an analytics tool (e.g. Watson Analytics, Power BI, Tableau, IBM Cognos, SAS, Rapidminer, etc) and develop innovative analytics solutions with regards to environment data, e.g. climate change, energy consumption, carbon footprint-GDP correlation, greenhouse gas emission, air quality-health impact, etc.

Some possible datasets/sources include:

Besides the suggested datasets/sources, you may apply any other real-world dataset to illustrate your approach (the different datasets/sources can be combined provided they are real-world data sources).


Submissions will be judged based on:

  • Creativity of the analytics solution

  • Quality of commentary and recommendations

  • Expected benefits for users and relevant stakeholders

  • Organization and presentation of the submission

Top 10 finalist teams will receive a finalist certificate for each team member and supervisor.

The top 10 finalists will be presented their prizes at the College Park Marriott Hotel & Conference Center, in Adelphi, Maryland (Washington DC), USA, during the 7th International Big Data and Analytics Education Conference hosted by University of Maryland University College, from June 3 - 4, 2019.


Teams are required to register by November 30, 2019.  Following registration, submissions will be due February 15, 2019. The submissions should include a report (with analytics screenshots and commentary, recommendations, etc.) and a 7 to 15 minutes video presentation link of the team’s solution (to be uploaded to YouTube). Your presentation document should explain the purpose and benefits of your solution. Feel free to make reasonable assumptions as needed.

View these sample videos from past year participants:

2018 First and Third Place Winners
2017 Winner