Android's Data Consumption

Android smartphones had the highest average data consumption compared to Apple. Android OS had consumed an an estimate of 2.2 gigabytes of data a month. Android’s competitor Apple iPhones had an estimate of 1.7 gigabytes a month consumed for data. Chetan Sharma, a telecom analyst for wireless carriers, also stated in the recent study that Android phones in the United States used an average of 4 gigabytes a month on average for 2013.

Nielsen

How big data scales will challenge these new and existing approaches. True, risks can put the entire enterprise at risk. If the organization has a risk management framework in place it can help address the most critical threats. We can look at using sophisticated analytics to improve overall decision making in these areas. The cloud will become a more standard platform. The market can be very demanding of the business model too. Timing is a crucial element. The company being able to sift through complex data sources and communicate critical data, how it delivers it new efficiencies and critical time saving information in real time. Advanced analytics technology helps to better leverage Big Data.

Who owns big data in the organization? Questions like these especially in the initial phases, being big data is a complex area are important. We have to define its objectives, identify these challenges and analytics to measure. Applying questions in the early phases is crucial.

Customer perspectives have come along way and now leveraging big data to segment and target customers experience shows us how powerful marketing, tools and the ROI can make real-time personalization possible.At this stage it appears executives are invested but we are now looking at the specific programs that are worth investing in. Those invested in Big data analytics and integration seek out fast response to BI questions and building competitive advantage, performance improvements.

Big data has now opportunity to identify new emerging data for organizations. Big Data is a substantial market. Most of our big data today has been produced in last two years alone. There seems to be many techniques to analyzing small data sets. Solution Providers can work to refine such approaches and techniques. Small data sets objectives should meet defined requirements, how to produce the best quality data derived and meet reliability from abundant data. Making sure the conditions are stable is also important. There are a environments that like migration style where some questions have to be answered such as using the right data migration tools. The larger project or environment the more complexities will arise.

U.S. economic pressures are vital to the health of a mobile organization’s survival. The impact of the economy on the insurance business impacts the entire consumer population which can greatly be affected by various economic factors. Mobile companies knowing what to anticipate for analytics and thinking ahead for long term outcomes will have better competitive advantages. Data is very critical to the Mobile Industry. Consumer expectations today demand companies to provide the most accurate, efficient and quality big data by incorporating multiple diverse data assets. Having the ability to identify and manage financial risks and monitor customer relationships requires organizations to develop more effective big data to provide deeper and accurate insights.  The use of quality big data will help in providing the right experience to customers.