Success Story

T-Mobile thrives thanks to data-at-scale initiative





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The leading mobile and 5G carrier sought an enterprise-wide data transformation to secure its data, maintain regulatory compliance, save time and reduce costs, and, ultimately, accurately predict customer behavior and intention. It turned to long-time partner Ataccama for its trusted solutions for complex environments. Ataccama has saved T-Mobile $350 million in cost-avoidance and consumer protection, and strengthened the competitive advantage of a global player in a notoriously challenging sector.

An enterprise seeks an enterprising solution

T-Mobile is one of the largest wireless carriers in the US, supporting over 116 million subscribers.

The globally recognised S&P 100 brand leads its market through superior customer experience and several high profile mergers and acquisitions, including its 2020 merger with rival US carrier, Sprint.

Its successes meant the organization was absorbing and handling more customers and their data than ever before, within an increasingly complex infrastructure. It also made it a target for attack. In 2021, a data breach and its direct impact on share price catalyzed T-Mobile’s efforts to redefine its data management at scale. It turned to long time partner Ataccama for expert advice and the solutions to support this mission.

The data governance team built a “Data Scanning at Scale” initiative. This meant scanning an estimated 5,000 apps and 22,000 databases continuously, with 8 petabytes of data.

Ataccama and T-Mobile enjoy a long-running partnership. T-Mobile employees are also its owners, via annual stock grants, and this transcends into a real responsibility that its teams feel to support the business and its customers. Ataccama greatly respects this commitment to the customer and, in turn, has worked hard to commit to being a trusted partner.

Other vendors are transactional in their behavior. With Ataccama, there's a genuine belief of shared responsibility of success that we feel within T-Mobile.”

Three objectives, one partnership, one solution

Three objectives stood out in allowing T-Mobile to secure its data at scale, remain compliant and activate its many data stores for actionable customer intelligence.

  1. Build a centralized management solution. This would automate audit balance control saving much needed time for T-Mobile
  2. Build a robust data quality solution. T-Mobile needed an enterprise-grade tool to scan large volumes of databases and quickly identify sensitive or PII data. This was in part directed by regulatory compliance, as well as a desire by T-Mobile to reference its data landscape in far more detail.
  3. Curate a single source of truth for internal and external data. The aim here would be operational efficiency as well as enterprise-wide trust in its data.

These three objectives could be delivered using one methodology: the “Data Scanning at Scale” initiative. Ataccama provided this within its unified platform for automated data quality, master data management and metadata management: Ataccama ONE.

It even works seamlessly in complex enterprise data governance contexts, such as T-Mobile’s.

The mobile carrier has to work with multiple IT, engineering and shadow IT organizations inside the company because of its federated distributed environment. This meant getting access to and scanning a large number of various data sources with structured and unstructured data located in on-premise and cloud environments.

This called for specific requirements:

  • Scan multiple systems at the same time;
  • Create new data labels to automatically classify new data sources;
  • Use accepted/rejected status to improve future scan success;
  • Seamless system integration;
  • Discover unknown applications and data stores for routine scans.

We wanted to master data management in the sales lifecycle and enhance the Data Mesh so our science teams better predict customer behavior and intention.”

T-Mobile ran a 24h proof of concept project; Ataccama, Oracle, Azure, Snowflake and AWS would parse through as much data as possible in that time.

Ataccama’s solution was ultimately selected. We managed to scan 138,972 tables and apply custom extraction rules to narrow the list to 22,494 tables of sensitive data. The speed has since increased to 800,000 tables in a 24-hour period.

Atacama was also chosen for its total cost of ownership, integration flexibility and future-proofing potential, as well as our relationship-driven approach to client success that T-Mobile has enjoyed now for over seven years.

Results that speak for themselves

The proof of concept was grown to the “Data Scanning at Scale” initiative.

This resulted in an automated, self-improving, closed-loop solution that onboards data sources, classifies data with automated rules and advanced machine learning, integrates with ticketing systems to create data remediation tasks, and provides reporting.

Over 22,000 databases and 5000 applications with over 8 PB of data were scanned and T-Mobile enjoyed significant benefits:

  1. $350 million in cost-avoidance and consumer protection by eliminating the risk of PII leakage;
  2. $50 million in savings through data reuse and removing redundant systems and databases;
  3. $25 million in savings by reducing data preparation times for AI teams.

The data governance team uses Ataccama ONE, continuously scanning systems, classifying data and securing newly added sensitive assets. The solutions also provides an always-on automated data scanning, classification and protection for existing and new data sources, and a solution for Data Mesh metadata gathering and disciplined, comprehensive data management.

The partnership between Ataccama and T-Mobile does not stop there. T-mobile is now in a stronger position to protect itself against third-party attacks, secure its data, comply with industry standards and turn its data into a competitive advantage to better serve its customers.

Ataccama has been pivotal in helping T-Mobile secure our vision of understanding our customers so well, we know when they have problems almost before they do.”

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