Telco operators are facing a massive opportunity for growth. As more users, devices and things get online, mobile networks are the common thread connecting these digital relationships.
From simple texting, to sharing documents with co-workers via mobile cloud, to calling a car with a ride-hailing app, the proliferation of mobile apps has transformed the way things work in the telecommunications industry. At the same time, emerging technologies such as 5G provide a new digital highway for transmitting more data than ever before. And all of this technology can capture incredible volumes of information about customer interactions.
Data has essentially become the new currency for telecom operators — the big data-driven telecom analytics market is expected to grow at a compound annual growth rate (CAGR) of nearly 49% between 2015 and 2020, accounting for $7.6 billion in annual revenue by the end of the period.
The problem is, legacy big data infrastructure solutions were not designed to handle the unpredictability of streaming data sources, nor were they designed to utilize data while fresh. In addition, telco operators have realized that location data plays big role in discovering new monetization approaches as well as deciding on physical areas and regions of investment. Now, telco operators must mine real-time data and instantly analyze it, translating raw data into instant insight that puts them ahead of the competition. With the growing number of data sources and increasing complexity of analysis, the key question for operators is: how can you leverage extreme data to retain customers and improve and expand your business operations?
We have defined the top five key ways telcos can use emerging technology that can leverage extreme analytics, to help them quickly collect and act on customer insights that ultimately hit the bottom line.
1. Analyze Network Usage & Call Records
To perform sophisticated analytics on live data, you need low latency between absorbing the data and querying it — done with aplomb by a GPU database. You will be able to quickly make sense of usage patterns, as well as identify network problems.
2. Monitor Usage & Capacity
A traditional relational database management system (RDBMS) is no longer sufficient to process vast volumes of complex streaming data in real-time or to conduct advanced location-based analysis. With extreme analytics, operators will be able to collect and visualize real-time data, from identifying the periods of heaviest network usage, to planning for possible network surges and outages, to forecasting network capacity.
3. Detect & Prevent Fraud
With a sophisticated analytics engine, operators can collect and analyze real-time data to detect unusual activity. This technology gives them the power to first model normal behavior, so they have a benchmark against which to measure. They can do this by analyzing usage data, account data, and location data. From there, they can build predictive models that can spot — and going forward, prevent — fraudulent activity.
4. Optimize Infrastructure & Network
To meet customers’ demand for instant and continuous connectivity, telco operators will need to be able to track and visualize the real-time usage and status of their networks, so they can gauge performance and identify any bandwidth or maintenance issues. Extreme analytics allow operators to perform real-time, predictive analytics that help them identify faulty equipment before it fails, leading to lower maintenance costs and fewer service disruptions. Being able to bring trained models to process and analyze the entire data corpus is a key capability that is required for optimizing operations.
5. Monetize Anonymized Customer Data
Google (GOOG) and Facebook (FB) are set to attract 84 percent of global spending in digital advertising, raising fears of digital monopolies. And lately, Google launched Project Loon, “a network of balloons traveling on the edge of space to extend internet connectivity to people in rural and remote areas worldwide.” Telcos need to catch up, and they have a bit of a leg up. Mobile device location data, combined with other subscriber data, provides information on what advertisements a subscriber has clicked on, at what time of the day, and from where they did it. Mobile data from a subscriber’s visit to a particular store, for example, paired with web browsing data, can help retailers deliver targeted ads to customers, or, going further, help them determine where to open their new retail locations. This is an unorthodox way for telcos to leverage their data into financial opportunity for them, while ultimately benefiting the customer through these kinds of integrated services.
In this new world, telcos need to translate massive volumes of complex data into digital insight at unparalleled speed, with streaming data analysis, visual foresight, and streamlined machine learning. Telco operators must embrace a new class of technology focused on accelerated parallel computing, and they can do that with a GPU-powered database. With so many significant opportunities on the horizon, the telecommunications industry needs to take the leap to stay competitive and achieve profitable change in today’s Extreme Data Economy.
Dipti Borkar is VP of Product Marketing for Kinetica.
Filed Under: Infrastructure
