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Real-time Analytics with Open-Source

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Real-time Analytics with Open-Source

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Working with big volumes of data is a complicated task, but it's even harder if you have to do everything in real time and try to figure it all out yourself. Over the past decades many open-source projects helped solve problems within the data analytics lifecycle around ingestion, storage, processing and visualisation of data. This session will use practical examples to discuss architectural best practices and lessons learned when solving real-time analytics and data visualisation decision-making problems with open-source at scale with the power of Amazon Web Services. It furthermore dives into a demo, using source code from the AWS Labs to visualise live data streams at scale.

Olivier Klein, Solutions Architect, Amazon Web Services, Greater China

Working with big volumes of data is a complicated task, but it's even harder if you have to do everything in real time and try to figure it all out yourself. Over the past decades many open-source projects helped solve problems within the data analytics lifecycle around ingestion, storage, processing and visualisation of data. This session will use practical examples to discuss architectural best practices and lessons learned when solving real-time analytics and data visualisation decision-making problems with open-source at scale with the power of Amazon Web Services. It furthermore dives into a demo, using source code from the AWS Labs to visualise live data streams at scale.

Olivier Klein, Solutions Architect, Amazon Web Services, Greater China

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