ROI of Big Data Analytics Native on Hadoop
by Hadoop_Summit on Jul 11, 2013
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Lacking the technology to directly leverage Hadoop, some companies are foregoing its full benefits opting to treat Hadoop as just another data source for their legacy BI tools. But storage is only one ...
Lacking the technology to directly leverage Hadoop, some companies are foregoing its full benefits opting to treat Hadoop as just another data source for their legacy BI tools. But storage is only one benefit of Hadoop and ignores its linear scalability and data flexibility across all data types. Using Hadoop natively for both storage and computation in an analytic capacity has already led to dramatic increases in business benefits. Hadoop analytics has already identified over $2B in potential fraud at one of the world’s largest credit card companies. Sears has already reduced reporting times over traditional BI from 12 weeks to 3 days. A major internet security company increased customer conversion by 60% and revenue by $20 million. Meaningful returns are spread across Fortune 100 enterprises and fast growing startups with the common thread being self-service big data analytics leveraging Hadoop’s native capabilities. In this talk, we’ll highlight the core value proposition of building analytics natively on Hadoop, share real-world use cases that resulted in dramatic ROI, and reveal the next major step in visual big data analytics.
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