Large organizations like YouTube are dealing with exploding data volume and increasing demand for data driven applications. Broadly, these can be categorized as: reporting and dashboarding, embedded statistics in pages, time-series monitoring, and ad-hoc analysis. Typically, organizations build specialized infrastructure for each of these use cases. This, however, creates silos of data and processing, and results in a complex, expensive, and harder to maintain infrastructure. At YouTube, we solved this problem by building a new SQL query engine - Procella. Procella implements a superset of capabilities required to address all of the four use cases above, with high scale and performance, in a single product. Today, Procella serves hundreds of billions of queries per day across all four workloads at YouTube and several other Google product areas.

The advent of smart infrastructure or Internet of Things (IoT) has enabled scenarios in which objects with unique identifiers can communicate and transfer data over a network without human to human/computer interactions. Incorporating hardware in such networks is so cheap that it has opened the possibility of connecting just about anything from simple nodes to complex, remotely-monitored sensor networks. In the paper, we describe a low-cost scalable and potentially ubiquitous system for indoor remote health monitoring using low energy bluetooth beacons and a smartwatch. Our system was implemented in a rehabilitation facility in Los Angeles and the overall assessments revealed promising results.