Faced with mounting data security challenges and a major breach, T-Mobile embarked on a data transformation journey to secure sensitive information, streamline compliance, and deepen customer insights. As Mark Venables explains by building a trusted data foundation, the company now leads in proactive data management, turning risk into competitive advantage.
T-Mobile, a leading mobile and 5G provider in the United States, recognised the pressing need for a comprehensive data transformation. With a customer base exceeding 116 million and a series of high-profile mergers, including its 2020 acquisition of Sprint, T-Mobile faced significant challenges in securing its expansive data landscape, ensuring regulatory compliance, and enabling more accurate customer insights. The catalyst for change came in 2021, when a major data breach not only compromised sensitive customer data but also impacted T-Mobile’s share price. This breach drove T-Mobile to redefine its data management at scale, setting the stage for an enhanced approach to data security and utilization.
Reflecting on this turning point, Daniel West, T-Mobile’s Data Management Lead, notes, “At T-Mobile, a breach where customer data was compromised became a catalyst for us to seek a robust data quality solution. This incident drove us to look for a tool capable of scanning and classifying data comprehensively. We already had a strong relationship with Ataccama for data quality, including centralized audit balance controls to manage data checks effectively. But we wanted to put it to the test, at T-Mobile’s scale, could a system scan thousands of databases and deliver the insight we needed?”
Securing and releasing data
T-Mobile’s objectives for this transformation were clear: establish a centralised management solution, implement robust data quality measures, and curate a single, reliable source of truth across internal and external data sources. These initiatives aimed to not only secure data but also activate T-Mobile’s extensive data stores for customer intelligence and regulatory compliance. With these goals in mind, T-Mobile launched its ‘Data Scanning at Scale’ initiative, a project that required both scale and precision.
“We needed data classification capabilities that would allow us to examine all our data connections across T-Mobile, particularly to identify any personally identifiable information (PII),” West says. “Using advanced machine learning and AI, we could now detect social security numbers, phone numbers, and other sensitive data, as well as flag government data, which has its own unique storage and access requirements.”
This solution provided T-Mobile with an enterprise-grade tool capable of scanning vast volumes of structured and unstructured data, both on-premise and in cloud environments. Navigating T-Mobile’s complex, distributed environment required a system capable of seamless integration across IT, engineering, and shadow IT divisions, ensuring a holistic view of the organisation’s data.
Survival of the fittest
To validate the solution’s capabilities, T-Mobile conducted an intensive 24-hour proof of concept, evaluating multiple vendors, including Oracle, Azure, Snowflake, AWS, and Ataccama. Ataccama ultimately emerged as the solution of choice, having scanned over 138,000 tables and used custom extraction rules to identify 22,000 tables containing sensitive data. This capability has since expanded, with Ataccama now able to scan up to 800,000 tables within the same timeframe, providing T-Mobile with a level of data governance previously unattainable.
“One of our primary objectives is to make T-Mobile’s data understandable, accessible, and trusted,” West explains. “By mastering data from sources like Dun & Bradstreet and other third-party providers, we gain a complete view of our T-Mobile for Business customers. With accurate customer data, we can route leads to the right sales teams more effectively.”
A transformative solution
As T-Mobile continued its data journey, two focal points emerged. “In terms of our data journey at T-Mobile, two main focuses stand out,” West continues. “First, we are expanding Master Data Management to enhance the sales lifecycle. Second, we are committed to ensuring that data entering our data mesh is accurate and consistent. This supports the process of transforming raw ‘bronze’ data into curated ‘silver’ and ‘gold’ data sets, which our data science teams can use to predict customer issues before they arise.” This level of refinement allows T-Mobile to anticipate customer needs, ultimately enhancing the overall customer experience.
The results of T-Mobile’s ‘Data Scanning at Scale’ initiative have been transformative. Today, T-Mobile’s data governance team uses the Ataccama One platform to continuously scan systems, classify data, and secure new sensitive assets as they emerge. This self-improving, closed-loop solution now scans over 22,000 databases and 5,000 applications, encompassing more than 8 petabytes of data. T-Mobile has realized substantial savings, including $350 million in cost-avoidance through mitigating PII leakage risk, $50 million through streamlined data reuse and the elimination of redundant systems, and $25 million by reducing data preparation times for AI projects.
“We have so much data about our customers, and our goal is to be smarter in understanding them and anticipating their needs,” West concludes. “The trust we have developed in our relationship with the team at Ataccama has been essential to reaching these goals.” By effectively managing its data resources, T-Mobile is now better equipped to protect against third-party attacks, comply with regulatory standards, and gain a competitive edge through data-driven insights.
Through this comprehensive data transformation, T-Mobile has not only fortified its data infrastructure but also positioned itself to leverage its vast data assets to enhance the customer experience. The trust established with Ataccama remains a cornerstone of this journey, providing T-Mobile with both the tools and confidence needed to navigate an increasingly data-centric future.
