Real time data analytics helps mobile service providers to achieve aggressive advantages

Usage of smart phone is become an integral part of our daily routine.  Keeping aside calling and SMS, we are always engaged with lots of other activities Staring from entertainment to domestic shopping, social engagement etc., by installing various types of mobile applications. Of course, mobile internet is mandatory to carry out above.  Mobile service providers are facing new and difficult challenges. Due to exponential growth of customer’s expectations, they need to serve accordingly with advanced mobile technology and handle unprecedented spikes in network traffic.  Time consumption is very high to persist/store huge volume of data and then analysed some later time to find the issues, faults, insights to improve service, maximise asset utilization and retain the most profitable customers etc.

Real-time data analytics significantly reduce the time consumption to address all the above-mentioned points since live data get processed during in flows, or streams, into the system. The major benefit of this is faster reaction times to the customers, business demands etc.  By leveraging real-time data analytics, major mobile service providers are cutting the time needed to analyse data from 12 hours to one minute approximately. Following are the steps generally involve in real time analytics

• Collecting the live data from the source probably huge volume of data. For mobile service provider, data volume might easily reach to thousand of gigabytes to terabytes that we can denote as Big Data.
• Continuous data flow via memory storage and during that short span of time the present technology can identify, track live data for issues, defects, abnormality, opportunities  etc
• Provide immediate response, feedback, enhancement etc to consumers

The beauty in this process is that data has not been persisted in storage area like RDBMS, Data Warehousing system for later analysis. Instead on the fly data gets processed and analysed by using temporary memory space.

Written by
Gautam Goswami

Can be reached for real-time POC development and hands-on technical training at gautambangalore@gmail.com. Besides, to design, develop just as help in any Hadoop/Big Data handling related task. Gautam is a advisor and furthermore an Educator as well. Before that, he filled in as Sr. Technical Architect in different technologies and business space across numerous nations.
He is energetic about sharing information through blogs, preparing workshops on different Big Data related innovations, systems and related technologies.