The flood of increasingly complex data that T-Mobile deals with put the wireless communications company on a path to continue to modernize its data strategy. That journey included a realization that turning to the cloud is not always a quick and easy answer to meet those growing needs.
In InformationWeek’s latest “That DOS Won’t Hunt” podcast, I talk to Vikas Ranjan, senior manager for data intelligence and innovation for T-Mobile, about forming and enacting a data modernization strategy as the mobile communications company evolves. He has been part of T-Mobile for more than 18 years and says the company’s data needs have changed with its operational direction. “Almost a decade back, T-Mobile was more of a traditional telecom service provider and our primary job was to make sure people were able to make phone calls and people were able to send their messages,” he says. “Our datasets and data platform were pretty simple at that time.”
Back then, database and data warehouse architects were central to T-Mobile’s data strategy, Ranjan says. Changes across the industry — from the rise of apps, location data, and other trends — led to changes at T-Mobile from a data perspective, he says. Customer growth also naturally has meant scaling up the data strategy. “Our data has exploded exponentially,” Ranjan says. “Just in the past eight years, our network logs, our network datasets have gone from a 10 terabyte to almost a petabyte scale.”
As the amount and complexity of data escalated, T-Mobile turned to the cloud, he says, for scalability and flexibility but with unexpected results. “That actually made our lives more difficult when it comes to the cost management,” Ranjan says. “The cost has become more unpredictable; the more you do in the cloud, you are not upfront investing and then leveraging the infrastructure. Everything you do in the cloud, with a single click, is adding more cost to you.”