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Big Data Unleashed Part 4: What Does “Mobile” Have To Do With Big Data?

 In my last blog, I discussed five areas of considerations for your information management agenda with Big Data. In the next three blogs, I will discuss how three secular trends, namely, Mobile, Cloud and Social are driving the evolution of Big Data.  In this blog, part four of the series, let’s explore “Mobile”. There are many reasons why people are fascinated by the impact of mobility.  According to Applied Mobility of Tech Trends 2011 by Deloitte, consumer interest in smartphones, tablets and untraditional connected devices such as set-top boxes, telematics, video games and embedded appliances is growing faster than any other product segment, with a projected growth of 36%. This staggering growth in mobility is driving the production and consumption of Big Data in three ways:

  •  People and devices are generating far more transaction data than before as it is cheaper and simpler to complete any transactions – buying books in a cafe with your iPad or completing banking transactions with a BlackBerry.  Transaction data growth is accelerating as more enterprises are adopting smartphones, tablets and other mobile devices, following the consumer trend.
  • As people and “things” are moving around further and faster, locational data combined with texts from social media, images, sensor, CDR, telematics data, and other interaction data pose unprecedented commercial opportunities as well as security and privacy challenges.
  • Big Data processing like Hadoop is tackling increasing diversity and volumes of data including application logs, network traffic logs, Web logs and user/customer data –mobility is fueling both production and consumption of Big Data.

Let’s face it – whether most people like it or not, they are being tracked.  This increased acceptance of “your location being tracked” is driven by increased surveillance, mandatory transportation check-ins and other location-based services embedded in devices.  In short, we need to be more diligent about exploiting  the opportunities while mitigating the privacy and security risks associated with mobility. Questions that we ask that are relevant to how to handle Mobility-related Big Data include:

  •  Are we ready to meet the end-user demand of fast and reliable access to data from their choice of application and device? Can we aggregate, resolve and combine a wide range of mobile streaming and other location-based data into meaningful, actionable and trustworthy insights?
  • Do we have the necessary technologies like middleware, caching, thin client applications and protocol supports? How do we support the data infrastructure impacted by the mobility enablers such as form factors, underlying networks, user interfaces and device computing power?
  • Are we ready to support compactness, resolution and response time tailored to mobile consumers and workers – do they have different personas and needs, and behave differently than other users?
  • What process changes do we consider to serve your customers and partners who are doing business now differently?
  • How do you apply the lessons learned from your mobile customers to improve your business? Ultimately are we solving real business problems and creating value?

 With mobile assets becoming pervasive and connected to other assets, organizations are seeking to build products and services in the mobile world. What is equally important is the potential for “mobilizing” business – empowering employees and partners to become more productive and supporting and collaborating with their customers who are changing their attitudes and behaviors freed by the use of mobile applications. This is now altering organizations from the bottom-up and impacting  brands as we alter how to interact with each other. As we imagine a world of mobility, we foresee new types of business opportunities arise above conventional boundaries, crossing geographies, industries and applications. This also means that we must operate beyond our traditional thinking about assumptions and sampled data because some interesting ideas, trends and patterns may be lurking at the edge where Big Data and “Mobile” meet.

To learn more, please check out how U.S. Xpress, a pioneer in transportation mobile intelligence, turned Big Data into big opportunities by combining mobility-driven data with their other data assets.

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