Instrumentation of processes and an organization's environment provides vast amounts of data that can be used to drive decisions. Next to setting up data collection, supervising data quality, and applying proper methods of analysis, organizations face the challenge to set up an infrastructure and architecture to do so efficiently and cost-effectively. Virtualized platforms such as private or public clouds are the method of choice for deployment, in particular for data analyses not occurring constantly. A cloud provider, either a commercial Cloud company or an IT organization within an enterprise, will like to set up a cloud platform such that clients can run big data workloads effectively on. Cloud customers would like to set up big data applications in a cost-effective and performant way on their platform. This keynote will walk through a few real life big data analysis scenarios from different industries and discuss the challenges Cloud providers face making trade-offs. Understanding those challenges and solutions help cloud users choose the right match between their algorithm, big data system and cloud platform.
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