Monday, January 14, 2019 — 10:30 AM EST
Verena Kantere
School of Electrical Engineering and Computer Science, University of Ottawa
Big Data analytics in science and industry are performed on a range of heterogeneous data stores, both traditional and modern, and on a diversity of query engines. Workflows are difficult to design and implement since they span a variety of systems. To reduce development time and processing costs, some automation is needed.
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