How T-Mobile Built a Data Platform For Analytics

In the contemporary data-driven era, a scalable and robust data platform is no longer a "nice to have" but a necessity for telecom operators’ business. It is essential for Communication Service Providers (CSPs)  to optimize network usage and services, enhance security, and improve customer experience. 

To explore this topic in detail, I was a guest on a recent TMForum Webinar, “Building a Data Platform to Support CSPs’ Analytics Ambitions”. The other participants were Mark Newman, Chief Analyst at TM Forum, and Vikas Ranjan, Senior Manager of Data and Analytics Engineering at T-Mobile. The webinar explored the options available for CSPs’ as they strive to improve their data platform strategies. 

Data Platform Trends

All three of us on the webinar have unique perspectives on the topic of building and optimizing data platforms, but we all agree that there are certain data platform trends that should be prioritized by data leaders. Over the course of the discussion, we explored how data observability addresses use cases to address many of the critical issues faced by data teams. 

The webinar was wide-ranging and informative, and covered these topics:

• Data platform modernization challenges
• Common approaches to data platform modernization 
• Cost management in a multi-cloud environment
• Organizational structure and governance to deliver an adequate data platform 
• How and where data platforms need to scale to maximize the potential of data use cases
• The costs of data reliability and quality
• What is Data Observability 

Here’s an overview of some of the key topics we addressed.

Paradigm Shift in CSPs

Vikas from T-Mobile discussed how rapidly advancing technology and growing customer demands are leading to a paradigm shift in CSPs. 

It is anticipated that by the year 2025, the global footprint for telecom usage will include 5B+ mobile users and 40B+ devices. This represents massive growth and will increase the demand for CSPs. Moreover, the rise of new businesses like metaverse and digital twin modernization, growing demands from Gen Z for streaming and social media, and increasing use of private networks and edge computing will require a paradigm shift in the way that CSPs provide services. 

Big data will play a crucial role in this wave of transformation for the communication industry. It can help the CSPs to realign their business strategies, make informed decisions, restructure their operations, and offer services in a manner that feels seamless to the customers. 

Data Platform Challenges 

In the webinar, we talk about the transformation that’s occurring in order to cope with the need for rapid, large-scale digital transformation. To deal with it, forward-thinking enterprises have changed their approach to a data-driven and customer-focused system. This has introduced various data platform challenges, including:

• Massive data volume
• Increased data complexity 
• The critical need for data reliability
• Cost optimization
• The impact of managing data in real-time
• Data engineering skills gaps

How Does Data Observability Help?

We also discussed how CSPs have been striving to enhance the availability, quality, and usability of their data for years. However, the evolution of IT environments has increased challenges for CSPs. Data has always been present across different applications, but now it is also spread across various cloud environments. It has increased difficulty in identifying where the issues may lie.

The discussion further highlighted how the use of Data Observability can help CSPs to meet the growing data demands by providing deeper insights into operational blind spots present in both on-premises and multi-cloud environments. 

According to Gartner's report, "What is Data Observability": “Data Observability has now become essential support as well as augment existing and modern data management architectures.” 

Acceldata Data Observability Platform

With the Acceldata Data Observability Platform, CSPs can get complete control over data and simplify data engineering. It provides an efficient way for CSPs to maximize data reliability, reduce spending, and eliminate operational blind spots. During the webinar, I highlighted the features and use cases of data observability that could help CSPs build a reliable and scalable data platform. 

Cost Optimization

With cloud cost optimization and cost optimization, Acceldata Data Observability can help in managing spend, allocating resources, and eliminating cost overruns.  

Data Reliability 

The Acceldata Data Observability platform can help CSPs to maximize data reliability by eliminating data outages. It can help them get detailed insights to prevent data issues. 

Operational Intelligence

Data Observability offers real-time insights that can help to optimize the cloud data platform by identifying the source of different issues in real-time with alerts and interactive dashboards.

Contact Us

No matter where you are on your data platform modernization journey, the Acceldata platform can help you achieve your goals. Reach out to us for a demo of the Acceldata Data Observability Platform and get started.

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Girish Bhat

SVP, Acceldata

@girishb

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