Processing concurrent time-series data
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Computer systems in energy, finance or cloud computing need to process time-series data that are produced concurrently by a number of data sources. In this talk, you’ll learn how to process and analyse such data in F# using agents.
We start with a brief introduction to asynchronous programming and then spend most of the time developing systems using re-usable agent based library. You’ll see that composing complex functionality is easy, if you have the right set of building blocks! At the end, we’ll also dive into the details of efficient agent implementation.
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Processing concurrent time-series data
Tomas Petricek
Tomas Petricek is a long time F# enthusiast, using F# since the early Microsoft Research versions. He has been a Microsoft C# MVP since 2004, and together with Jon Skeet wrote Real-world Functional Programming which explains basic functional concepts using C# 3.0 (teaching F# alongside) and which shows several appealing real-world uses of F# and functional techniques. He also contributed to the development of F# during two internships at Microsoft Research in Cambridge.
Simon Cousins
Simon Cousins is a software developer actively applying muti-paradigm programming techniques to solve complex problems within enterprise applications.