Recorded at Launch Fishers in Fishers, IN on 10-12-18
PyData Indy 2018
So you've learned about the data analytics capabilities of Python, and now you're ready to start churning through data -- great! But do you know how to turn your snippet of code into a system capable of taking in streams of raw sensor data and spitting out insights? This presentation will lay out the basic components of a Python-based data pipeline built for Internet-of-Things (IoT) applications, and will highlight some of the common challenges associated with putting together an efficient data analytics and storage system.
Key topics include:
• An overview of cloud-based "serverless" data pipelines;
• Pros and cons of locally-hosted or "edge computing" systems;
• Tradeoffs between cost, scalability, complexity, and development time for different architectures
By the end of this presentation, you will have gained a broad overview of the ecosystem needed to support a Python analytics solution: how to get data in and out, how to write and deploy scalable code, and how to manage system cost and complexity.
Негізгі бет Ғылым және технология "Building IoT Data Pipelines with Python" by Logan Wendholt
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