Implementation of the First Big Data Initiatives with Hadoop for a Telecommunications Multinational

01The Client

Telecommunications multinational with operations in the Brazilian market, at an early stage of Big Data technology adoption.

02The Challenge

• Lack of infrastructure capable of processing and storing the large volumes of data generated by telecom operations
• Limitations of traditional relational tools for data analysis at scale
• Need to enable advanced analytical use cases (churn, network quality, customer experience) with large-scale data
• Lack of internal expertise and defined architecture to start the Big Data journey

03Implemented Solution

• Deployment of the Hadoop ecosystem as a Big Data platform for ingestion and processing of large data volumes
• Definition of data architecture and configuration of the distributed environment (HDFS, MapReduce, Hive, Sqoop)
• Construction of data ingestion pipelines from the company's main operational sources
• Development of the first analytical workloads and exploratory models on the platform
• Technical training of internal teams for platform operation and evolution

04Strategic Differentials

• Pioneering Big Data adoption in the Brazilian operation, creating analytical competitive advantage
• Architecture designed to scale progressively, supporting new use cases without rework
• Knowledge transfer to the internal team, ensuring autonomy and platform continuity
• Pragmatic approach focused on high-value use cases for the telecom business (churn, quality, experience)

05Results Achieved

• Unprecedented ability to process and analyze data at scale in the Brazilian operation
• Technological foundation established for continuous evolution in advanced analytics and predictive models
• Enablement of analyses that were previously unfeasible with traditional tools
• Reduction in processing costs compared to previous proprietary solutions