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 is a computer scientist and open-source developer. He is a Visiting Researcher at the Alan Turing Institute working on tools for open data-driven storytelling. He wrote a popular book called "Real-World Functional Programming" and is a lead developer of several F# open-source libraries.
Simon Cousins
Simon Cousins is a software developer actively applying muti-paradigm programming techniques to solve complex problems within enterprise applications.