T-Mobile's Data and AI Evolution with Connected Data Architecture
OVERVIEW
EXPERIENCE | In Person |
---|---|
TYPE | Breakout |
TRACK | Data Governance |
INDUSTRY | Media and Entertainment |
TECHNOLOGIES | Data Sharing, AI/Machine Learning, Governance |
SKILL LEVEL | Intermediate |
DURATION | 40 min |
T-Mobile Network Engineering team has been working with Databricks Lakehouse for years to help solve the massive scale (up to 600Tb/day of ingest) challenges. We can now link previously siloed subscriber data assets to network data across a unified multi-tenant data platform facilitated by Unity Catalog. This modern Lakehouse approach streamlines collaboration, reducing data duplication, complexity, and costs. Enhanced data sharing accelerates innovation by breaking down data silos.
We will discuss the results we have seen with Unity Catalog, simplifying setup and governance for both data providers and recipients and enhancing performance while supporting notebook sharing, AI models, governance, auditing, and lineage. Databricks Unity Catalog catalyzes the enablement, experimentation, and realization of several corporate initiatives: network performance, coverage analytics, churn prediction, data-driven marketing, fraud detection, and delivering exceptional CX.
SESSION SPEAKERS
Vikas Ranjan
/Senior Manager, Data Intelligence
T-Mobile
Anand Muttayane
/Member of Technical Staff
T-Mobile