T-Mobile's journey to turn crowdsourced big data into actionable insights
Who is this presentation for?Business leaders, data analysts, data engineers
Voice calling is one of the key services provided by cellular network operators and the most important performance measure of this service is the audio quality. This session highlights how T-Mobile leveraged multiple teams to implement a crowd-sourced solution to measure and respond to audio quality metrics, and to put data into the hands of decision-makers.
Turning this Big Data idea into an action requires multiple teams with different expertise. Mobile device engineers and radio frequency engineers are essential to invent the mechanism of measuring the audio quality and to test it in the lab. Technical account managers are a key link to persuade the cell phone manufacturers to implement the mechanism on the phones. Another major link comes from data scientists and data engineers who enable easy interaction with the massive amount of data. Finally, data analysts interpret the data and find the correlations needed to turn the big data into insights. When combined with the field engineers who tune the configuration to run the test, the solution can be deployed and iterated upon rapidly. Making a real change out of the big data is a journey of achieving one same goal with collaborations among many teams.
Crowd sourcing starts with identifying the data to collect. From the research in the lab, a mechanism was invented to detect the audio quality without having to listen to the actual audio. This mechanism was implemented in the cell phone software, then the mechanism was verified in the lab for data integrity and to ensure minimal impact on the battery performance. The software has been delivered to millions of cell phones to enable daily reporting of the audio quality.
In a collaboration with the field team in LA for a limited trial, the collected audio quality data was put to a practical use. A correlation analysis was performed to identify the network parameters that are most predictive of the audio quality so that they can be tuned empirically in the field. A dashboard and an interactive heat map were created to track the changes in the audio quality with the different parameters in multiple trials and to conclude on the configuration which provides the best audio quality.
Scaling up to apply the change at the national level was a new challenge. Billions of records are collected each month and crunching this data to generate the dashboard pages and heat maps required an efficient system to handle the huge data volume. To tackle this problem, we made a massive investment in computing power, capitalizing on state-of-the-science open source distributed computing technology. By combining the scalability of Hadoop services like the Hadoop Distributed File System, Kudu and Spark with powerful user-focused analytics engines like Alteryx, Terabytes of data can be ingested on demand into visualization tools such as dashboards and maps in minutes.
This presentation will focus on the challenges faced in this large-scale crowd sourcing and data analytics project and how T-Mobile solved them to ultimately accomplish the original goal of improving the quality of experience for end users. In addition, some unexpected benefits from big data analysis will be shared to highlight the unique advantages of big data.
Prerequisite knowledgeThis presentation is for teams who already are working with data in some way, who are struggling to grow or implement large-scale solutions. No specific background is necessary as long as the audience members are excited to see real world data problems being solved.
What you'll learn
Alex leads the cell phone based big data crowd sourcing and analytics strategy at T-Mobile. He identifies the use cases of big data, defines the technical requirements for data collection, crunches the crowd sourced data and visualizes the results to steer the business decisions. He won the Innovator of the Year in 2017 for delivering the 5GHz band utilization analysis for unlicensed LTE deployment strategy.
Alex has 19 years of the mobile industry experience in areas from radio frequency engineering, product marketing and big data analytics. He is using all the experience to make his big data analytics create bigger value and make practical differences.
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