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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

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 User Experience” and “Store Manager Actionable Dashboard”), I discussed how critical it was to the success of your big data initiatives that you identify and understand upfront how to deliver the analytic insights and recommendations in a manner that is actionable (and measurable).   Virtual and augmented realities provide yet another mechanism that can be leveraged to deliver analytic insights and recommendations to key business constituents, including your customers and channel partners.

Google Cardboard, Google’s virtual reality viewer, when coupled with a smart phone provides an economical platform for the delivery of the analytic insights and recommendations to the key business constituents (see Figure 1).

Figure 1: Google Cardboard Virtual Reality Viewer

For example, let’s say that an organization wants to apply big data (data + analytics) to improve predictive maintenance of their key products.  Organizations could leverage these augmented reality and virtual reality platforms in a predictive maintenance scenario to help mechanics, technicians and engineers to know exactly where the problem resides, what specific parts and components fix and with what parts.  Heck, the augmented reality solution could even provide the relevant installation and maintenance instrumentations based upon the problem being fixed and the experience and certifications of the mechanic, technician or engineer doing the work (see Figure 2).

Figure 2: Predictive Maintenance Augmented Reality Mockup

The data captured during the installation work could prove invaluable across a number of customer-centric use cases including mitigating warranty liabilities, mitigating substitute and counterfeit part issues that might lead to future safety and performance problems, increasing yield and performance effectiveness, improving customer satisfaction, etc.

Summary
Augmented reality has the potential to deliver the analytic results and recommendations directly to the business constituents including customers and channel partners.  Augmented reality and virtual reality are quickly becoming viable deliver platforms for our big data initiatives.

Besides, if you can’t deliver the analytic results in a way that is actionable to the key constituents, then why bother with the analytics at all.

Oh dang it, one of those annoying Rattatas snuck into the house and is attacking Amelia while she’s studying…er, uh… watching “Keeping Up with the Kardashians”!  Where’s the dog when you need him!


1. A technology that superimposes a computer-generated image on a user’s view of the real world, thus providing a composite view

The post Pokémon Go and Its Role in a Big Data World appeared first on InFocus.

More Stories By William Schmarzo

Bill Schmarzo, author of “Big Data: Understanding How Data Powers Big Business”, is responsible for setting the strategy and defining the Big Data service line offerings and capabilities for the EMC Global Services organization. As part of Bill’s CTO charter, he is responsible for working with organizations to help them identify where and how to start their big data journeys. He’s written several white papers, avid blogger and is a frequent speaker on the use of Big Data and advanced analytics to power organization’s key business initiatives. He also teaches the “Big Data MBA” at the University of San Francisco School of Management.

Bill has nearly three decades of experience in data warehousing, BI and analytics. Bill authored EMC’s Vision Workshop methodology that links an organization’s strategic business initiatives with their supporting data and analytic requirements, and co-authored with Ralph Kimball a series of articles on analytic applications. Bill has served on The Data Warehouse Institute’s faculty as the head of the analytic applications curriculum.

Previously, Bill was the Vice President of Advertiser Analytics at Yahoo and the Vice President of Analytic Applications at Business Objects.

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