About Speaker
Olivier has been working for Amazon Web Services across Asia-Pacific and Europe with a strong focus on building resilient, scalable, secure and cost effective application architectures. Together with various incubators and accelerators, he actively assisted startups to adopt a lean and agile concept to build platforms that align revenue model with their IT infrastructure spending, effectively reducing waste and disrupting how product development has been executed over the past decades. Entrepreneurial agility is driven through quick iterations of lean and quantifiable developments in Olivier’s beliefs, the reason he has worked with key customers and partners to build intelligent analytics platforms using industry best practices to repeatedly streamline service usage, reduce costs and increase customer satisfaction. Prior to his AWS time, Olivier was responsible to run the digital product strategy for an educational book publisher across Asia and he actively lead key development efforts in building a virtualised web service platform for a Luxembourgish Internet Service Provider.
About the Topic
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 AWS. It furthermore dives into a demo using source code from the AWS Labs to visualises live data streams at scale.