Authors :
Dr. Chandrasekar Shastry; Abirami Thangavel
Volume/Issue :
Volume 7 - 2022, Issue 11 - November
Google Scholar :
https://bit.ly/3TmGbDi
Scribd :
https://bit.ly/3mTyfxq
DOI :
https://doi.org/10.5281/zenodo.7731137
Abstract :
Operators of telecommunications are sitting
on a gold mine. They produce enormous amounts of
data each day, up to billions of CDRs and events. These
data could be user, network, or customer-related. For
the telecommunications operators, effectively gathering,
storing, processing, and analyzing this amount of data
can be very difficult. The infrastructure must have
ample storage space and computational power.
Additionally, it needs adaptability to assess various data
formats. Therefore, it is crucial to create the best
architecture possible in order to overcome these
technical difficulties and satisfy commercial needs.
In this paper, we have used the seven layers of
implementation described in the previous work and
implemented a potential use case- churn analysis of
telecom customers. We have also analyzed various other
use cases along with case studies and have proved how
our open source data pipeline architecture would help
the telecommunication sectorsto implement and analyze
those use cases.
Keywords :
Implementation of Open Source Data Pipeline for BDA, Customer Churn Analysis, Churn Analysis Code, Big Data Analytics, Telecom Use Cases for BDA, Open Source, Lambda Architecture, Big Data Architecture Layers, Telecommunication, Telecom BDA Use Cases.
Operators of telecommunications are sitting
on a gold mine. They produce enormous amounts of
data each day, up to billions of CDRs and events. These
data could be user, network, or customer-related. For
the telecommunications operators, effectively gathering,
storing, processing, and analyzing this amount of data
can be very difficult. The infrastructure must have
ample storage space and computational power.
Additionally, it needs adaptability to assess various data
formats. Therefore, it is crucial to create the best
architecture possible in order to overcome these
technical difficulties and satisfy commercial needs.
In this paper, we have used the seven layers of
implementation described in the previous work and
implemented a potential use case- churn analysis of
telecom customers. We have also analyzed various other
use cases along with case studies and have proved how
our open source data pipeline architecture would help
the telecommunication sectorsto implement and analyze
those use cases.
Keywords :
Implementation of Open Source Data Pipeline for BDA, Customer Churn Analysis, Churn Analysis Code, Big Data Analytics, Telecom Use Cases for BDA, Open Source, Lambda Architecture, Big Data Architecture Layers, Telecommunication, Telecom BDA Use Cases.
