Data Exploration and Analytics

Our research focuses on data exploration and data analytics algorithms and systems to help various kinds of users to gain insights from their data. In particular, we focus on solutions that apply on what is commonly referred to as Big Data, i.e., large amounts of highly heterogeneous data that need to be processed at high-speed.

Healthcare analytics

As part of a collaboration with the National University of Singapore, we investigate data engineering solutions for healthcare applications. 

Recommendations

To interactively explore data sets, users profit from some guidance of what to explore next. This requires methods that recommend queries to users that possibly lead users to new facets of the dataset not explored so far. As gaining insight from data is commonly significantly eased through proper visualizations of the data, recommendations of visualizations for the explored data are necessary. In this context, we are researching novel recommendation methods for query and visualization recommendation for data exploration in databases.

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