Big data analytics
The technologies that support big data are now widely available, lowering the entry barrier for communication service providers (CSPs) to take the next step: revenue generation. The initial big-data issues represented by the three Vs – volume, variety and velocity –have been overcome. Through innovative database design, faster networks and the availability of open-source tools to handle the variety of big data, the focus has shifted to the three As: adequate, accurate and actionable – just enough accurate data to take revenue-generating action.
A generation shift has occurred, moving the issues associated with big data a step higher up in the analytics chain. The question is no longer about the technology; today the question is how to create value from the vast amount of data available. In other words, it’s not about how big the data is, but rather about what data will bring insights that will in turn generate revenue.
Analytics-generated insights will help CSPs identify seemingly inconsequential pieces of data that, when combined with other network data, can be crucial for revenue generation and identifying early signs of churning.
The new view of big data is supported by cutting-edge IT components in terms of data storage, data management and network resources. By putting operational analytics closer to the data source, CSPs can optimize network utilization and create new products and sources of revenue.
It’s all about insight – smarter networks, improved user experience, data monetization and churn prevention.
http://www.ericsson.com
A generation shift has occurred, moving the issues associated with big data a step higher up in the analytics chain. The question is no longer about the technology; today the question is how to create value from the vast amount of data available. In other words, it’s not about how big the data is, but rather about what data will bring insights that will in turn generate revenue.
Analytics-generated insights will help CSPs identify seemingly inconsequential pieces of data that, when combined with other network data, can be crucial for revenue generation and identifying early signs of churning.
The new view of big data is supported by cutting-edge IT components in terms of data storage, data management and network resources. By putting operational analytics closer to the data source, CSPs can optimize network utilization and create new products and sources of revenue.
It’s all about insight – smarter networks, improved user experience, data monetization and churn prevention.
http://www.ericsson.com
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