Our client, a prominent telecom company headquartered in Texas, is a participant in the federal Lifeline Support Program. The company’s focus lies in delivering prepaid mobile phones and service bundles to underserved individuals.
Hours delivered back to the business
SOX compliance in Settlement process automation
Success rate of bot case completion
For functional release of OBT, RTS and OGS
The Challenge
In a collaborative effort, our proficient analytics team was tasked with conceiving and executing a comprehensive data management and analytics platform. The objective was to enable our client to aggregate data from diverse sources, gain valuable insights into customer behavior, harness historical data for analysis, and facilitate predictive capabilities. An additional challenge was to manage access permissions effectively, as the client sought to furnish their partners with access to pertinent tenant-specific analytics.
What did Dignifyd do
We developed a robust data analytics platform that cleverly aggregates data from 10+ sources, including user interactions, tariffs, devices, and apps. Our adept big data team used the MQTT protocol to seamlessly channel telemetry data into Apache Kafka, while Amazon Spot Instances optimized AWS costs. Scalability was ensured through AWS Application Load Balancers.
Apache Kafka efficiently organized raw data for transfer to Amazon Simple Storage Service and Amazon Redshift. This repository housed telemetry data from Android devices and intelligence from ERP and HLR sources. Dignifyd’s ROLAP cubes facilitated routine and ad-hoc reporting, tracking impressions, click-throughs, and gauging customer satisfaction through support call correlations.
Our innovative solution extended to client tenants, granting valuable insights. Two access paradigms were introduced: shared access, managed at the data warehouse level, and dedicated access via separate AWS accounts, benefitting telecom partners with their own customers and HLRs.
The Results
- Data collected via MQTT and channeled into Apache Kafka.
- Amazon Spot Instances optimize AWS costs and AWS Load Balancers ensure scalability.
- Valuable insights provided to client tenants, enhancing their understanding of customer behavior and trends.
- Apache Kafka organizes raw data for transfer to Amazon Simple Storage Service and Redshift.
- ROLAP cubes enable routine and ad-hoc reporting, tracking impressions, click-throughs, and gauging customer satisfaction.
