Big data analytics lets carriers identify and solve network issues
ATLANTA — In the crowded and competitive carrier space, network operators are looking for the best ways to leverage big data analytics to keep up with consumer demand.
According to a 2014 Cisco report, U.S. consumers lead the global pack by using an average of 1.38 gigabytes of data per month, up from 752 megabytes in 2012.
Jake Kasper, data services manger of Illinois-based rural carrier Cellular One, highlighted challenges during an educational session at this week’s Competitive Carriers Association Global Expo.
In Cellular One’s case, the company had three main problems: a major slow down in the speed of data services between 2:30 p.m. and 4:30 p.m., poor coverage near a main tower, and a hot zone in a picturesque downtown area where building codes prevented the deployment of indoor coverage.
Working with consulting group ClearSky and its analytical modeling tool NetView360, Cellular One said it was able to precisely identify bottlenecks in their network through the use of big data. Cellular One’s slowdown issue turned out to stem from a public high school where data use surged as classes let out between 2:30 and 4:30, coupled with a grain tower that hampered signal strength.
For both of these problems, Cellular One was able to adjust its infrastructure accordingly.
For the hot zone issue, the ClearSky solution showed that the glass storefronts of most buildings would not hamper the signal of additional outdoor small cells.
ClearSky’s approach, which was enthusiastically demonstrated by Albert Rubio, VP of professional services, uses a similar tact as other big data systems like CompStat, the system used by most police departments to track and predict crime patterns. The system uses data hot spots combined with other data such as peak hours, and the number of internal walls in structures, to identify bottlenecks and problem areas and make recommendations to solve such issues.
