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Dean of Big Data

William Schmarzo

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Top Stories by William Schmarzo

I was reading an interview with John Krafcik, CEO of Google’s Self-driving Car Project, in the August 8th issue of Bloomberg BusinessWeek. The article referenced a survey by AlixPartners where they found that 73% of people wanted autonomous vehicles.  But when people had the option to have a steering wheel in the car, allowing optional full control to the driver, the acceptance rate jumped to 90%.  This finding, that people are much more accepting of automation and new ideas when they have the option of control, is totally consistent with what we found with respect to how to deliver big data analytics. The big data engagements we run for EMC focus on applying predictive and prescriptive analytics to deliver recommendations to help key decision makers become more effective at at their jobs.  For example, delivering recommendations to teachers in how to best group th... (more)

Pokémon Go and #BigData | @BigDataExpo #IoT #M2M #BigData #Analytics

Yep, I play Pokémon Go.  I take joy walking around the neighborhood and in strange towns catching a Pinsir, Ponyta, or Growlithe or two (though I have to put up with those pesky Ekans, Paras and Spearows).  You see, I play Pokémon Go for …er, um,… research purposes.  I can’t help but to imagine how organizations can leverage “augmented reality[1],” the secret sauce behind Pokémon Go, to deliver analytic insights and recommendations to key business constituents in a way that is more direct and actionable (not to mention measurable). In previous blogs (see “Analytics, Meet the Use... (more)

Do Your Big Data Analytics Measure or Predict? | @BigDataExpo #IoT #M2M #BigData #Analytics

Organizations have key business processes that they are constantly trying to re-engineer. These key business processes – loan approvals, college applications, mortgage underwriting, product and component testing, credit applications, medical reviews, employee hiring, environmental testing, requests for proposals, contract bidding, etc. – go through multiple steps, usually involving multiple people with different skill sets, with a business outcome at the end (accept/reject, bid/no bid, pass/fail, retest, reapply, etc.). And while these processes typically include “analytics” that... (more)

A Harsh Message for Big Data Vendors | @BigDataExpo #BigData #Analytics

This is a short blog with a harsh message for Big Data vendors. Camera fades in to Pastor Schmarzo heading to the pulpit… What does the future hold for today’s Big Data vendors?  Hundreds of startups are rushing into the Big Data market to stake their claim to a market that IDC predicts will reach $187 billion by 2019.  Dang, that’s a big market, especially considering that the Global Business Intelligence market will only reach a trifling $20.8 billion by 2018 or the long-running ERP applications market is expected to reach a trivial $84.1 billion by 2020.  Yes, the big data mar... (more)

Tips for Data Scientists | @CloudExpo #BigData #IoT #DigitalTransformation

I spend a lot of time helping organizations to “think like a data scientist.” My book “Big Data MBA: Driving Business Strategies with Data Science” has several chapters devoted to helping business leaders to embrace the power of data scientist thinking. My Big Data MBA class at the University of San Francisco School of Management focuses on teaching tomorrow’s business executives the power of analytics and data science to optimize key business processes, uncover new monetization opportunities and create a more compelling, engaging customer and channel engagement. However in work... (more)