Personalized healthcare, learning engagement analytics and climate change are a few of the areas where this week’s Big Data & Analytics Hero Nitesh Chawla has uncovered “gold nuggets.” Learn more about his experiences and see what he thinks is still missing for big data and analytics to really deliver ROI.
Should tomorrow's generation acquire analytic skills no matter the degree? Why or why not?
I equate analytic skills as equivalent to problem-solving skills and being inherently curious. Analytics starts with asking questions, leveraging data to drive answers to the questions and marshaling those answers to actions. The next generation should acquire the skills through taking course work in programming, databases, data mining, machine learning, statistics, related quantitative courses and projects, especially team-based projects requiring real-world data. There are so much more data and tools readily available online, and only curiosity is the limit. Children can be naturally gifted in generating hypotheses and validating (or refuting) them based on their experiences. Why not put some structure around it as part of curriculum right from elementary school?
What is the market still missing for big data and analytics to really deliver ROI?
I believe that big data and analytics will be the game changer in the competitive landscape, and the companies that quickly, but judiciously, engage data-driven culture and thinking may have the edge. Innovation is not just about technology in this case, it is also about people, culture and mindset. At times there can be a last mile problem—that is, the technology as an enabler is there, but it has to be translated through an execution to have an ROI. We need an infusion of careful construction and validation of hypotheses in the decision making process, which is, in many ways, a combination of domain knowledge, intuition, data and computational thinking and processes.
What "gold nuggets" have you uncovered using big data and analytics?
My research program in big data and analytics at Notre Dame is strongly focused on developing novel data and network science algorithms and computational frameworks that transform discovery of the "gold nuggets" with greater accuracy and speed. Our research is making fundamental contributions in the areas of link prediction in networks, modeling dynamics and evolutionary processes in social networks, graph-based methods for anomaly detection, learning from imbalanced data (rare events), mining big data and deployment and evaluation issues for data science algorithms. Our research is also bridging disciplinary boundaries for transformative applications in healthcare, education, environment and national security; technology meets society is a theme. We are founded on the principles of big data for the common good, and tackling the big challenges facing our society today.
To name a few nuggets in the applications domain:
Our work in personalized healthcare has uncovered the promise of rapid advances toward disease management and wellness. We have developed a health and wellness personalization engine and successfully translated it to the community from chronic disease management, to obesity and diabetes management for adolescents, to aging well for seniors.
Our work in learning analytics reveals that electronic portfolios can be quantitatively and qualitatively analyzed to generate learning engagement analytics that indicate the level to which students are surviving or thriving during their first-semester intro to engineering course. This information can provide instructors, teaching assistants and advisors critical early warning signs that can help with STEM retention.
Our work in adaptation for climate change includes the Notre Dame Global Adaptation Index. Decision-makers use ND-GAIN’s country-level rankings to determine how vulnerable countries are to climate change and how ready they are to adapt, thus informing strategic operational and reputational decisions.
- Our work in social networks uncovered processes that given formation of new links and evolution of networks as a function of link formation and influence propagation of a node. This has significant impact on applications such as viral marketing, epidemiology, information diffusion and security.
View all of our Big Data & Analytics Heroes here on the Hub, and look out for next week's Hero: Jesse Harriot, chief analytics officer at Constant Contact.