For the past 8 years, those interests have centered around the confluence of near real-time data processing and big data. Over the years, I’ve pursued those interests through the CEDR streaming research project, which defined the basic algebra and query processing algorithms for streaming queries, the StreamInsight data processing product, which made this technology available to Microsoft customers, and most recently Tempe, which focuses on the visualization of ad-hoc streaming queries, and Trill, which processes streaming and temporal queries at unprecedented levels of performance, resulting in a one size fits all engine for tempo-relational analytics. Trill is widely used within Microsoft, including in the Azure Streaming Analytics Service, and in Bing advertising. This work has taken me on a fascinating journey, and has resulted in some unanticipated discoveries, such as Ping-Pong Patience Sort, and deterministic progressive analytics. Prior to working on near real-time data processing and big data, I’ve pursued interests related to SQL materialized views, SQL query optimization, high speed data compression, and high dimensional indexing.