Session: How T-Mobile implemented data observability with their platform modernization

Vikas Ranjan, Senior Leader, Data Intelligence & Innovation @ T-Mobile

Vikas joins us to share how T-Mobile has developed a comprehensive strategy for data platform modernization and general engineering best practices from a Tier-1 telecommunication provider.

He will walk through his perspective on how to de-risk data platform migrations and accelerate migration initiatives. Attendees of this session will learn how data observability has helped throughout the modernization journey from a legacy ecosystem to an open source and cloud native platforms such as Databricks and Snowflake.

Go Deeper: Building a data platform to support CSPs' analytics ambitions

Watch the webinar recording here

This recorded webinar explores the options and capabilities that are available to communication service providers (CSPs) as they seek to optimize their data platform strategies.

CSPs have been striving to improve the quality, availability, and usability of their data for many years. But the evolution of IT environments and partnerships are combining to make that task even more challenging.

Data has always been spread across multiple applications and systems but now it is also spread across multiple cloud environments. This makes the task of identifying where issues, or problems, may lie with the data incredibly difficult.

Watch the webinar replay to learn:

  • How to track and manage costs in a multi-cloud environment
  • How and where data platforms need to scale to leverage the potential of data and AI/ML use cases
  • The hidden costs of data quality and reliability
  • The concept of data observability – what it means and what it delivers.
  • Organizational structure and governance to deliver an optimal data platform and strategy

Presenters:

  • Vikas Ranjan - Sr. Manager, Data & Analytics Engineering, T-Mobile
  • Girish Bhat - SVP of Marketing, Acceldata
  • Mark Newman - Chief Analyst, TMForum

 

What is the cost to attend the virtual sessions?

EDS is always free and open for all to attend.

What is Enterprise Data Summit?

Enterprise data teams are moving from dashboards and reports to powering AI agents, real time decisions, and mission critical products. At large scale, that work is shaped by platform choices, governance, cost pressure, and the realities of operating complex data systems inside large organizations.

Enterprise Data Summit is a focused day for leaders who are modernizing AI ready data platforms. It is where enterprise data engineers, platform and analytics leaders, AI and ML teams, and partners in finance, risk, and security compare notes on how to ship reliable data and AI systems at scale.

Who comes to EDS?

  • Data and analytics engineering

  • Data platform and architecture

  • AI, ML, and LLM platforms

  • FinOps and cloud cost management

  • Data governance, security, and risk or compliance

Join us for talks that include:

  • Designing AI and agent ready data platforms, including lakehouse, streaming, and vector or retrieval layers

  • Using generative AI to accelerate data work while keeping quality, lineage, and controls in place

  • Data and AI governance as the control plane for trust, access, and regulatory compliance

  • FinOps for data and AI, including unit economics, chargeback models, and practical cost controls

  • Operating models for enterprise data teams, from platform teams to data products and self service

  • Data and AI reliability and observability in production, including real incidents and lessons learned

  • Hybrid and multi cloud data strategies, sovereignty, and regionalization in regulated environments

  • Moving from AI pilots to an enterprise AI platform backed by durable data foundations

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