University of Minnesota
Software Engineering Center

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Exploring the Structure of Data at Scale

Date of Presentation: 
Wednesday, January 16, 2019
Presented By: 

Understanding the underlying structure of data is frequently a key first step in exploratory analysis. It can be especially difficult when the data set is large and might be high dimensional in its features. For a retailer it might be providing product recommendations. For an insurance company it might be modeling risk or fraud. When dealing with millions of records it can be quite challenging to pick up potentially valuable patterns and shapes.

This talk will provide an overview of approaches that can be used to explore, visualize, and understand the structure of data. After covering the conceptual ideas, the primary focus will be on practical usage, specifically on various open source and commercial packages that can be readily leveraged.