How a telecom giant fast-tracked data lake implementation - Impetus

How a telecom giant fast-tracked data lake implementation

Machine learning implementation on data lake led to 6% increase in customer acquisition


One of the top 3 US-based telecom providers wanted to migrate from an Oracle data warehouse to a Cloudera Hadoop-based data lake to take advantage of advanced analytics. The existing analysis mechanism was unable to increase net new and upgraded conversions. They were looking for a partner to analyze their customer journey and set up a modern Cloudera -based data lake that would help them:

  • Reduce the cost of data management and analysis
  • Effectively utilize their marketing budget
  • Get better insights to grow their B2B lead generation
  • Improve the effectiveness of marketing campaigns and channels
  • Increase business revenue

6% increase in customer acquisition for omni-channel data


The Impetus team analyzed the existing data from RDBMS and external systems like Salesforce and Marketo and created a Hadoop data lake on the Cloudera (CDH) cluster for lead generation. These datasets were mined and mapped to enhance lead generation and conversion.

The solution involved implementing cross-sell/up-sell, continuum, lead-generation, and multi-touch-point attribution models to enhance marketing campaign effectiveness. Audit-trail policies were also applied to monitor and handle failovers.


  • Used Kerberos on CDH cluster for authentication and authorization
  • Added email notifications to all the ML models to monitor data ingestion workflows for failovers
  • Tested all ML models and ingestion workflows
  • Enabled optimization by tuning the hyperparameters in the property files without any change in code


The solution helped develop an end-to-end customer-360 journey, migrated data and ingestion pipeline, and modernized the existing lead generation models.

Business benefits

  • Increased revenue by lead generation and conversion
  • Effectively utilized campaign budgets
  • Reduced cost of data storage
  • Increased capability to store and analyze data

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