Presented By O'Reilly and Cloudera
Make Data Work
22–23 May 2017: Training
23–25 May 2017: Tutorials & Conference
London, UK

Schedule: Enterprise adoption sessions

16:3517:15 Thursday, 25 May 2017
Location: Capital Suite 10/11
Level: Beginner
Vijay Agneeswaran (Walmart Labs)
The class of big data computations known as distributed merge trees was built to aggregate user information across multiple data sources in the media domain. Vijay Srinivas Agneeswaran explores prototypes built on top of Apache HAWQ, Druid, and Kinetica, one of the open source GPU databases. Results show that Kinetica on a single G2.8x node outperformed clusters of HAWQ and Druid nodes. Read more.
16:3517:15 Thursday, 25 May 2017
Location: Capital Suite 15/16
Level: Non-technical
Andy Petrella (Kensu)
Average rating: *****
(5.00, 1 rating)
Data science for enterprise use cases explodes the number of intermediate datasets. Thus, one of upcoming challenges is to find a way into these ever-growing data sources. Andy Petrella proposes a data-science-on-data-science approach, using behavioral data combined with static and runtime metadata of processes. Read more.