Making Sense of IoT Data

A session at Big Data Week 2015

IoT = Big Data! In this talk we are going to discuss the latest development in Big Data, Machine Learning and Data Science, and use real IoT use cases to cover lifecycle of IoT data analytics: capturing, storing, cleaning, analyzing, predicting and maintaining.

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Charles Cai

Large trading system architect, photographer and fly fisherman. Follow me for latest technology in mobile, social coding, investment banking and energy trading. bio from Twitter

Charles Cai has more than two decades of experience and track records of global transformational programme deliveries – from vision, evangelism to end-to-end execution in global investment banks, and energy trading companies, where he excels at designing and building innovative, large scale, Big Data systems in high volume low latency trading, global Energy Trading & Risk Management, and advanced temporal and geospatial predictive analytics, as Chief Front Office Technical Architect and Head of Data Science. He’s also a frequent speaker at Google Campus, Big Data Innovation Summit, Cloud World Forum, Data Science London, QCon London and MoD CIO Symposium etc, to promote knowledge and best practice sharing, with audience ranging from developers, data scientists, to CXO level senior executives from both IT and business background. He has in-depth knowledge and experience Scala, Python, C# / F#, C++, Node.js, Java, R, Haskell programming languages in Mobile, Desktop, Hadoop/Spark, Cloud IoT/MCU and BlockChain etc, and TOGAF9, EMC-DS, AWS CNE4 etc. certifications.

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Date Wed 25th November 2015

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