Being an early adopter of new technologies that serve business, Verizon started its Big Data analytics journey very early and is doing exciting things with its data since then. As their business grew, they developed innovative solutions to cater to the growing analytical needs of their business users. At a recent session at Strata Data Conference in San Francisco, Syed Latheef, Head of Analytics at Verizon, spoke on how they utilize Kyvos as a next-generation analytical platform that delivers real-time AI, ML, and BI.
Challenging Big Data Landscape
With millions of subscribers in the US and thousands of B2B customers around the world, Verizon was collecting massive amounts of data from various sources such as POS, call center operations, social media, websites, and many more. They wanted to analyze this data in real time to deliver one-to-one customizations to their existing subscribers as well as bring in more customers into their spectrum.
There was no shortage of data, but the challenge was to enable solutions that would help them harness this data. Their goal was to leverage data to power their marketing decisions and improve their customer experience. To solve these business challenges, Verizon decided to take its Big Data analytics platform to the next emerging technology.
AI, ML, and BI on Big Data
They brought in high-speed data from batch processes, real-time streams, IoT, connected devices, and more, into their Big Data platform and then built AL and ML models on top of it. Once they built their data pipeline, they use Kyvos on top of it for analytics. Kyvos immediately made petabytes of data available to their business users for slicing and dicing. It helped them build a presentation layer so that they could understand what was happening, how they were moving against the KPIs, and what exactly was the benefit of all the data that they were collecting.
Kyvos enabled several functionalities for their business users and provided a lot of flexibility in understanding the data and sifting through analytics. “Kyvos is both a starting and end-point for us. As data comes in from batch processes, real-time, IoT, connected devices, and more, we leverage Kyvos to analyze it and understand what it has for us. And then, once the AI pipeline fills, we again use Kyvos to check the accuracy, outcome, or any lift in our models”, said Syed.
Meeting Real-time Business Needs
Today, Verizon leverages its Big Data to meet the real-time needs of their business. Their analytical platform helps them identify friction points, detect anomalies on the fly, and fix issues instantly. For example, they can monitor their call center operations in real-time and use the data to send predictive as well as prescriptive triggers. Let’s take the case where a front-line executive at the call center exceeds the threshold time in responding to a call. Once the system detects that a call is taking more time than expected, it sends alerts that can be pushed immediately to the front-line channel so that they can take corrective actions while still on the call. Similarly, there are predictive triggers where after a particular time has elapsed, the system can predict that the call may exceed the threshold limit, prompting the front-line managers to intervene and resolve the issue.
Similarly, in the case of their video set-top box division, they can analyze viewership data in real-time and use it for advertisement insertions. The data is analyzed as soon as it comes in and helps them decide which ads to pop-up depending upon the channels their users are watching.
If you want to know more about Verizon’s solution or see how Kyvos can help you build a modern analytical platform, request a demo now.