Discover How Telcos Do Hadoop. Not all of the purposes will appeal to everyone (rummaging around in age-old CDRs is obviously not possible in all legislations), but here you go:
- Analyze call detail records (CDRs). HDP facilitates long-term data retention for root cause analysis of dropped calls, even years after the first issue.
- Service equipment proactively. HDP stores unstructured sensor data from the network. Telcos can apply machine-learning algorithms to this data and derive optimal maintenance schedules by comparing real-time information with historical data.
- Rationalize infrastructure investments. Using HDP to store and analyze network log data, telcos can understand service consumption in a particular state, county or neighborhood and invest accordingly.
- Recommend next products to buy (NPTB). An HDP-based data lake gives telco salespeople the ability to make confident NPTB recommendations, based on data from all customers.
- Allocate bandwidth dynamically. With historical network data, operators visualize spikes and nimbly throttle bandwidth. This helps them maintain service quality and customer satisfaction, and also informs strategic planning to build smarter networks.
- Develop new products. An HDP-based data lake puts rich product-use data in the hands of product managers, speeding product innovation. Immediate feedback on product launches allows PMs to rescue failures and maximize blockbusters.
If you don’t feel like giving all kinds of personal information away just yet to the nice folks over at Hortonworks, here is a direct link to an informative, yet marketing-laden document.