Time series, a data type long neglected by Silicon Valley, is finally seeing its time in the sun with investors opening their wallets. TimeScale, a startup adding time series capabilities to Postgres closed its $16M series A in January; InfluxData closed its $35M series C in February to continue developing its time series platform; and PingThings, Inc. is currently raising its series A.
While much of the recent activity is being driven by server monitoring metrics and the rising Internet of Things, time series data comes from a variety of sources from time stamped events arriving asynchronously to sensors continuously measuring physical processes. Further, time series data permeates numerous disciplines including economics and econometrics, finance, DevOps, medicine, and most of the sciences and engineering.
In this presentation, Sean and Michael will examine the time series ecosystem with a focus on the various data stores and platforms that are purpose built for this data at scale and the various categories of analysis techniques that can be performed on this data. The presentation will then go in depth into a particular open source sensor analytics platform in detail, discussing some of the data structures and architectural decisions that enable performant time series analytics at scale.
Michael Andersen is an EECS PhD student at the University of California, Berkeley working on technology for a secure internet of things. This includes high performance time series databases for next generation high-density telemetry, energy efficiency through Software Defined Buildings, and resiliency through instrumentation and analysis of smart grids. BTrDB originated in his PhD research into scalable analytics on grid data.
Sean Patrick Murphy (https://www.linkedin.com/in/seanpatrickmurphy1/) is the co-CEO of PingThings, Inc. (http://www.pingthings.io/), an AI-focused startup founded in 2014 bringing advanced data science and machine learning to the nation’s electric grid. After earning dual undergraduate degrees with honors in mathematics and electrical engineering from the University of Maryland College Park, Sean completed his graduate work in biomedical engineering at Johns Hopkins University, also with honors. He stayed on as a senior scientist at the Johns Hopkins University Applied Physics Laboratory for over a decade, where he focused on machine learning, high-performance and cloud-based computing, image analysis and anomaly detection. Switching from the sciences into an MBA program, he graduated with distinction from Oxford. Using his business acumen, he built an email analytics startup and a data sciences consulting firm. Sean has also served as the chief data scientist at a series A-funded health care analytics company and the director of research and instructor at Manhattan Prep, a boutique graduate educational company. He is the author of multiple books and several dozen papers in multiple academic fields. He co-founded and served as a long-time board member for Data Community DC and the Data Innovation DC Meetup.
• 6:30pm -- Networking and Refreshments
• 7:00pm -- Introduction, Announcements
• 7:15pm -- Presentation and Discussion
• 8:30pm -- Data Drinks (Tonic , 2036 G St NW)