5 Myths About Spark and Big Data (And Where It Goes Next) - Databricks

5 Myths About Spark and Big Data (And Where It Goes Next)

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For such a young area of technology, there sure seems to be a lot of rigid assumptions on how to do “big data” the right way. Leveraging current ESG research, this session will explore some of the common misconceptions around Spark and Hadoop, where they are coming from, and how a better understanding can set you up for success. Topics will include: -Who is responsible for your overall big data strategy, anyway? – How long will it take for a Spark initiative to add real business value? – What matters most in evaluating vendors offerings? – Why does open source matter to Spark?

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About Nik Rouda

Nik is a senior analyst covering big data, business intelligence, analytics, visualization, and other technologies that help people understand what is happening in their business. He enjoys working with early stage investors in validating both products and business models. He has a broad IT background spanning both infrastructure and applications, a customer-focused perspective, and extensive experience in marketing and technical sales worldwide