Massive amounts of data are generated every day – from weather and traffic patterns to disease outbreaks and even banking transactions. The stories these datasets tell are important ones, but it takes a trained ear to listen.
Associate Professor of Computer Science Sangmi Pallickara is hearing them out. “Big data analytics allows users to analyze the information immediately and make decisions based on what we learned from data,” said Pallickara. “Ultimately, this leads to smarter decisions, more efficient operations and insights.”
Her research focuses on big data for the sciences, with an emphasis on issues related to predictive analytics, storage, retrievals and metadata management. For her work, Pallickara was one of three researchers across the globe to receive the 2018 Award for Excellence in Scalable Computing for Middle Career Researchers, presented by the Institute of Electrical and Electronics Engineers Technical Committee on Scalable Computing.
Connecting the dots
“The goal of big data analysis is effective knowledge discovery from voluminous, high-velocity datasets,” said Pallickara. “You want to analyze the huge, fast changing dataset, extract any useful information and use that information to make an accurate forecast of what will happen – all before our decision becomes too old to be useful. That can be only a few seconds”
Pallickara’s work focuses on datasets with two characteristics, containing trillions of data points, each with important information. “Understanding how these features interact with each other is challenging and fun!” she said. Her projects have been deployed in agricultural sciences, atmospheric science and meteorology, environmental monitoring and epidemiology.
Pallickara has also received a National Science Foundation CAREER Award for her work.