BIG DATA use cases – are there any “killer apps”?

Are there any Big Data “killer apps”? The quick answer is “No”.

The Hadoop framework is being applied to many use-cases. Even though Hadoop has been in the public domain since Yahoo! began investing in scaling Hadoop from an interesting prototype back in 2005 to the robust scalable framework it is today, the “kill app” is still difficult to spot.

The application of the Big Data technology is broad. That is why we’re seeing companies like Cloudera, Hortonworks, MapR on the infrastructure; Hadapt, Quantivo, ClickFox, and others on the analytics; a new breed of simple query/BI tools like Datameer….all scaling quickly to address the growing market need….not to mention the many companies using the Hadoop framework.

When I share ideas with various technology providers, there’s the typical response to “What’s the killer app?”…it includes web mining analytics, content optimization/personalization, advertising, recommendations, sensor data analytics, and even spam detection.

In the graphic above, I’ve attempted to categorize BIG DATA use-cases / applications from a sample of over 100 companies. Some of these categories could be combined. I tried to focus on the answer to the question, “what’s the leading use-case?” because many companies are applying the Hadoop framework to several internal use-cases.

What’s your “killer app?”

[Note: Of the above sample, the average node cluster configuration was 508. If we remove extremes, the average drops to 52 nodes.]

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Jim Kaskade

Jim Kaskade is a serial entrepreneur & enterprise software executive of over 36 years. He is the CEO of Conversica, a leader in Augmented Workforce solutions that help clients attract, acquire, and grow end-customers. He most recently successfully exited a PE-backed SaaS company, Janrain, in the digital identity security space. Prior to identity, he led a digital application business of over 7,000 people ($1B). Prior to that he led a big data & analytics business of over 1,000 ($250M). He was the CEO of a Big Data Cloud company ($50M); was an EIR at PARC (the Bell Labs of Silicon Valley) which resulted in a spinout of an AML AI company; led two separate private cloud software startups; founded of one of the most advanced digital video SaaS companies delivering online and wireless solutions to over 10,000 enterprises; and was involved with three semiconductor startups (two of which he founded, one of which he sold). He started his career engineering massively parallel processing datacenter applications. Jim has an Electrical and Computer Science Engineering degree from University of California, Santa Barbara, with an emphasis in semiconductor design and computer science; and an MBA from the University of San Diego with an emphasis in entrepreneurship and finance.