Welcome to the Data Systems Group

The Data Systems Group at the University of Waterloo's Cheriton School of Computer Science builds innovative, high-impact platforms, systems, and applications for processing, managing, analyzing, and searching the vast collections of data that are integral to modern information societies — colloquially known as “big data” technologies.

Our capabilities span the full spectrum from unstructured text collections to relational data, and everything in between including semi-structured sources such as time series, log data, graphs, and other data types. We work at multiple layers in the software stack, ranging from storage management and execution platforms to user-facing applications and studies of user behaviour.

Our research tackles all phases of the information lifecycle, from ingest and cleaning to inference and decision support.

  1. June 23, 2020Brad Glasbergen, Michael Abebe, Khuzaima Daudjee, Daniel Vogel and Jian Zhao receive Best Demo Award at 2020 ACM SIGMOD Conference
    photo of Brad Glasbergen, Michael Abebe, Khuzaima Daudjee, Daniel Vogel, Jian Zhao

    Cheriton School of Computer Science PhD students Brad Glasbergen and Michael Abebe, along with Professors Khuzaima Daudjee, Daniel Vogel and Jian Zhao, have received the Best Demonstration Award at the 2020 ACM Special Interest Group on Management of Data (SIGMOD) Conference.

  2. May 29, 2020Waterloo-based AI start-up Inductiv acquired by Apple
    photo of Professor Ihab Ilyas

    Waterloo-based Inductiv Inc., an AI start-up that uses machine learning to automate the task of identifying and correcting errors in data, has been bought by tech giant Apple.

  3. May 11, 2020DSG researchers use technology-assisted review to find effective treatments and procedures to mitigate COVID-19
    photo of Maura R. Grossman and Gordon V. Cormack

    Since the COVID-19 pandemic began, researchers and clinicians have rushed to understand the available treatments and procedures to mitigate this rapidly growing threat to human health. The sheer volume of studies published on COVID-19 — in countries spanning the globe — as well as lessons learned from prior epidemics and pandemics, simply cannot be gathered and assessed quickly enough using traditional manual methods during this time of crisis.

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