Big Data Solutions

CDR-Case-Study

CDR Data Analytics, Enhanced 911 Data Sync and Real-time SIP Utilization Solution using Big Data Technology

Summary

AppleTech designed a solution with the big data technology to tackle CDR analysis, 911 Data Sync for emergency responders and Real-time SIP utilization optimization.

Challenges

There were 3 main challenges that needed to be addressed:

  1. Handling huge volumes of the CDR data and providing useful metrics to customers for reviewing their call patterns.
  2. Swift sharing of accurate phone number and address with the emergency response database.
  3. Real time monitoring of call quality issues to ensure optimal utilization of SIP.

Solution

Using big data technology, a comprehensive solution was developed which was not only able to handle the data but also provide powerful metrics to the customers to review their call usage patterns based on day, time of the day, numbers, completion status and many more critical parameters. This became particularly useful and important as the volume of such data is huge which makes life difficult for telecom companies and operators. It also affects the consumers and law enforcement agencies who are trying to retrieve the data for analytical purposes.

The solution also increased the speed of sharing the accurate phone number and address with the emergency responders. In emergency situations, every moment is critical and quick communication about the exact phone number and location of the incident, to the relevant authorities could spell the difference between a good and a bad outcome.

Access to real-time SIP Utilization data was made possible for customers and telecom providers to monitor and optimize the traffic bandwidth and take swift corrective action to maintain call quality over the internet connection. This becomes very handy when there is a need of an uninterrupted communication for critical meetings or decision making processes.

Tech Details

The solution has been built on a backend framework of .NET and a frontend framework of Angular. Since the solution deals with bulk data, the regular SQL databases won’t be able to handle it. Hence Elasticsearch was preferred as it has the capability of dealing with big data for its storage, search and analysis in a swift and near real time manner.

Features

  • Telephony Updates through Software
  • Manage Call Forwarding
  • Manage Caller ID Updates
  • Phone # to SIP linkages
  • CDR Analytics
  • Accurate Address Validation
Skills

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Posted on

December 4, 2020