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.
Monday, January 14, 2019 — 4:00 PM EST
Christian Gorenflo, PhD candidate
David R. Cheriton School of Computer Science
Blockchain technologies are expected to make a significant impact on a variety of industries. However, one issue holding them back is their limited transaction throughput, especially compared to established solutions such as distributed database systems.
