Smartphones’ Growing Popularity Creates Massive Data Challenges
Smartphone owners are now the majority of mobile phone users, increasing from 49 percent of U.S. mobile subscribers at the beginning of the year to 56 percent in the third quarter, according to new data from Nielsen.
“Google remained the top Web brand,” the firm wrote in a Dec. 20 blog posting, “with an average 172 million unique visitors each month between January and October 2012, followed by Facebook, which garnered an average of 153 million visits each month.”
That’s good news for a number of groups, including smartphone manufacturers and apps developers. However, it also hints at the challenges confronting any firm that depends in some way on data from mobile devices. More smartphones running more apps and video equals a tsunami of information flooding into data centers across the country on a minute-by-minute basis. Calling that a challenge to store, manage and analyze is like deeming the Atlantic Ocean a lovely little pond.
In addition, part of that rise in smartphones comes from more organizations giving their workers increasingly higher-powered mobile devices on which to perform daily tasks (that is, if they haven’t subscribed to a Bring Your Own Device policy). That creates still another challenge for the data-wranglers of the world: how to best craft mobile apps capable of processing and analyzing massive datasets?
The answers to both those questions—how to handle the flood of data coming in via mobile devices, as well as design apps capable of delivering data in the best possible way to that same handheld hardware—are necessarily complex. In the building-apps category, there are certain fundamental things to consider, such as security and best programming practices; and because data scientists and software developers need to eat, there’s also the question of the best way to effectively monetize Big Data apps.
On the “how to handle the flood of data” side of that question, the answers are much less clear-cut. Massive organizations have the money and engineering power to effectively store and analyze data from untold numbers of customers; for example, Facebook created some rather ingenious systems, including the custom-built Corona platform, in order to handle its billion subscribers. Smaller organizations, at least, can depend on cloud services such as Amazon’s new Redshift to help solve their data-wrangling issues—but that doesn’t mitigate the challenges presented by the rise of Big Data.
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