Databases Reference
In-Depth Information
Big Data Analytics for Telecom
If there is any industry that has been truly in the thick of unprecedented data growth,
it is the telecommunication industry; innovations and offerings like smart phones, mobile
broadband services, peer-to-peer information sharing and video-based services have all
played significant roles in contributing to this data growth. In addition, the omnipresence of
mobility solutions in all aspects of a consumer's life is redefining how products and services
are accepted or discarded by customers. Historically, the telecom operators had always had
data on their subscribers, their usage patterns, network performance, cell-site information,
device level data, as well as billing data and customer-service-related data. However, most
of this data resided in the siloed data repositories; they were not organized, and analyzed in
a collective way to provide greater insight into customers and their preferences.
The telecom business is also a capital-intensive business, especially in developing and
deploying the infrastructure to serve and support an ever-growing consumer base. Thus,
a top business priority for a telecom company is to keep delivering new revenue- generating
and customer-satisfying services but without overloading infrastructure capacity and
network performance and without costs running out of control. In essence, for telecom
operators to survive the competition and stay profitable, they need to get a micro-level
view of the services they provide, and they need smarter decisions in real time taking into
account all critical aspects of their business.
Figure
3-3
illustrates a typical telecom applications landscape overlaid with type of
data sources (structured or unstructured) and big data characteristics.
Figure 3-3.
Telecom applications and systems
