Telecom Analytics: 5 Use Cases With a Fast SQL Database

telecom towers

Why telcos need a fast SQL database that can add context and personalization to streaming data.

For telecommunications providers, the time to modernize to gain a competitive advantage is here. Legacy telcos, mobile carriers and CSPs (communications service providers) are faced with growing competition, and a string of merger news from companies like ATT/Time Warner, Level 3 Communications/CenturyLink, and Verizon/Yahoo hints at tectonic shifts in the telecommunications world.

Despite turmoil in the competitive landscape, telcos have an opportunity to prosper. This is due to the massive amounts of customer data at their fingertips, as well as the fact that telcos have ownership over their own networks. For these reasons, telco applications need a fast operational SQL database that not only captures and analyzes streams of data, but also adds context and personalization to the data, acting on it in real time before important insights and opportunities are lost. Here are five telco applications in which a fast operational SQL database brings an important competitive advantage:

Telecom analytics: five use cases


In today’s consumer landscape, it’s no secret that customers want a highly personalized user experience. If telcos can provide an accurate and customized user experience to their subscribers on any of their devices, in real time, customer churn reduces and loyalty increases. Service providers can also build newer and better service promotions and offerings by targeting users through real-time actions on fast data streams. By using a really fast (in-memory) database as part of their solution, they can achieve what we call hyper-personalization and be able to achieve the goal of the right offer to right person at the right time.

Correct billing (OSS/BSS)

Telcos have tight network efficiency guidelines. They oftentimes rely on business support systems (BSS) and operations support systems (OSS) software to handle policy management, billing management, and bill mediation to minimize expenses and reduce the costs of bringing new services to market. For these applications, real-time analytics on streams of data are invaluable. Fast data solutions enable real-time analytics on vast streams of incoming data, enabling the automated, real-time decisions mandatory for OSS/BSS applications. Other alternatives such as traditional databases are generally too slow to ingest incoming data streams, and are thus unable to perform real-time analytics and make real-time decisions on the incoming data. To ensure precise billing, real-time analytics paired with transactions is the way to go.

SLA management

It is mandatory that calls placed in a network meet the service level agreement (SLA) requirement of responding in 50ms or less, 99.999 percent of the time, in order to authenticate the call. To avoid customer dissatisfaction, a call is often connected even if the call authorization request is not received quickly enough. However, the customer is not billed, which can negatively impact revenue. The calling customer can also be refused connection, resulting in a network outage – and customer dissatisfaction. Thus, fast data processing is crucial.

Subscriber management

It is critical for service providers to manage and monitor user sessions in real time to guarantee a seamless, personalized experience. To do so, user data needs to be processed very quickly from the network, and analyzed and monitored in real time on an individualized, per-event basis. For example, fast databases can analyze subscriber data in real time based on certain event triggers, like the end of a call, data usage thresholds, and device usage in certain locations.

Session management

To provide a flawless user experience, service providers must keep a very close eye on the data produced by millions of user sessions. This means they must have the capability to analyze and monitor data in real time on an individual basis. With real-time analytics, providers can pinpoint users from device ID data and then connect it to data streaming from in-progress sessions to ensure a continuous experience for customers across their first and second screens. When it comes to fast event data such as media segment requests and media inventory search requests, the data gives the context necessary for each data point or event to be identified, and thus contributes to a seamless customer experience across devices.

For any telco software solution, even the smallest delay in ingesting, monitoring, analyzing and acting on subscriber data can lead to customer churn, missed SLAs, increased opportunities to interact with subscribers, and subscriber dissatisfaction. By implementing a fast operational SQL database solution, telcos and CSPs are able to handle high volumes of incoming data and take action on streams of data in real time before important insights, and even customers, are lost.


In-memory computing

Use cases: customer experience management

Dennis Duckworth

About Dennis Duckworth

Dennis Duckworth is director of product marketing at VoltDB.

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