Collecting and analyzing big data can offer new insights into things such as consumer behaviour, disease prevention, business trends, and electoral forecasting. It has become an increasingly relevant topic in the digital age, with corporate and government entities investing millions into big data research.
However, processing vast amounts of data that are integrated from different sources can lead to errors and inconsistencies. That’s why Chiang is building software tools to automate and improve data quality so that users can spend more time and resources on data analysis and decision-making.
“Organizations spend about 80 per cent of the data analysis time on resolving inconsistencies before companies can actually gain knowledge and insight from data,” explains Chiang, computing and software assistant professor. “This is a big challenge as it wastes a lot of time and money.”
Chiang and her research group work with prominent industry partners like IBM to improve their data quality. Chiang believes industry opportunities are vital for students during their graduate studies.
“Making connections with industry gives students the opportunity to address industry challenges now.”
Developing a close connection with students is important to Chiang. She meets with students regularly to talk about their research and opportunities for growth. She also encourages students to be independent thinkers. “Students need to think beyond conventional approaches to develop technology that has broad impact.”