ISB Datathon Case Competition competition highlights the speed and accuracy of SymphonyAI’s approach to enterprise AI
SymphonyAI, a leader in high-value enterprise AI software solutions for strategic industries, announced it earned first place in the ISB Datathon Case Competition 2021 for advanced analytics and data science. The success illustrates how SymphonyAI’s focus on clarifying how different variables are connected in an explainable manner, rather than simply seeing how variables cluster without understanding the connections, delivers better results faster.
The Indian School of Business Institute of Data Science hosted the Business Analytics Datathon in November and December 2021, challenging the data science community to leverage advanced analytics and data science to deliver business solutions that facilitate transformational decision-making.
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In the ISB Datathon Case Competition, teams’ solutions are assessed by ISB professors and research directors, along with industry leaders and executives at leading corporations. The 2021 competition concluded at the institution’s Data Science Summit on December 4. SymphonyAI’s team focused on a problem within the retail vertical with a data set of 19.5 million daily sales records and designed a solution in ten days to forecast and analyze multivariate store and product behavior. Apart from being the winning solution, the approach was appreciated for its novelty.
“We examined 699 products across 144 stores and needed to determine in a short amount of time how to forecast sales behavior accurately while taking into account a wide range of possibilities and despite missing crucial pieces of information,” said SymphonyAI Vice President of AI and Data Science Sudarson Roy Pratihar. “Our method succeeded because we can see the shape of the data and understand the meaning of it, rather than discovering associations among attributes of data. For example, standard methods might see an image of a hand as a bunch of pixel points. But the SymphonyAI approach understands the specific shapes of fingers or a wrist from those points, and that these shapes connect in specific ways that allow the hand to move and do what it does. We can see and explain underlying drivers and how they’re connected faster and better to drive clear and accurate decision-making.”
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