Big data Self-service analytics is the solution to two critical issues that big data organizations are experiencing: the proliferation of data and the subsequent shortage of data scientists to capture, manage, and analyze it all. To bridge the gaps and to take business analytics beyond what legacy reporting tools can do, many organizations are implementing self-service solutions that enable users to extract more value from ever-growing data volumes. When today’s cloud platforms are combined with modern big data performance solutions, data analysis power users can leverage self-service to quickly gain business insights, optimize scaling, and create a unified interface to simplify analysis. Join us as we discuss the best practices for simplifying big data analytics while providing data analysts and scientists with self-service access on AWS cloud. Watch this webinar to: • Understand why more organizations are moving to the self-service analytics model. • Learn how to more easily create elastic Hadoop, Spark, and other big data clusters for dynamic, large-scale workloads. • Learn the best practices for cost optimization of big data workloads. • Understand how to evaluate big data SaaS criteria and determine whether “as-a-service” is right for your big data. • Learn the best practices for implementing big data self-service analytics.


19:00 - 20:00 hs GMT+1


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