Elevating Sustainability: Tervita Corporation's Data Pipeline Revolution with Tasrie IT Services

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Elevating Sustainability: Tervita Corporation's Data Pipeline Revolution with Tasrie IT Services


The case study explores the collaboration between Tasrie IT Services and Tervita Corporation, focusing on upgrading Tervita's data pipeline infrastructure to enhance smart mobility insights.

Client Background:

Tervita Corporation Provides a background on Tervita Corporation, emphasizing its role as a leading environmental and energy services company, and its mission to enhance sustainability and efficiency through smart mobility insights.

Problem Statement:

Highlights the challenge faced by Tervita due to an outdated data pipeline, hindering effective processing and utilization of connected vehicle data.

Solution Provided by Tasrie IT Services:

  • AWS (Amazon Web Services): Recommended for scalability, reliability, and security.
  • Debezium: Chosen as the change data capture tool for real-time changes in MySQL database.
  • Apache NiFi: Used for efficient data integration, movement, and transformation.
  • Apache Airflow: Orchestrated complex workflows and scheduled Spark jobs for data processing.
  • Hadoop Distributed File System (HDFS): Leveraged for scalable and fault-tolerant storage.

Implementation Process:

Outlined a phased approach:

  • Assessment and Planning: Analyzed existing infrastructure and developed a migration plan.
  • AWS Cloud Migration: Transitioned to AWS for a scalable and secure cloud environment.
  • Debezium Integration: Captured real-time changes in the MySQL database.
  • Apache NiFi Configuration: Optimized data flow within the AWS ecosystem.
  • Apache Airflow Workflow Implementation: Designed and scheduled Spark jobs for data processing.
  • Testing and Optimization: Rigorous testing at each stage, fine-tuning configurations for efficiency.

Results and Benefits:

  • Real-time Data Processing: Enabled by Debezium, ensuring minimal delay in analysis.
  • Scalability and Flexibility: AWS adoption provided flexibility for growing data volumes.
  • Efficient Data Flow: Apache NiFi optimized the ingestion and movement of connected vehicle data.
  • Workflow Automation: Apache Airflow facilitated timely execution of Spark jobs.
  • Fault-Tolerant Storage: HDFS ensured reliable storage, reducing the risk of data loss or system failures.

Future Considerations:

  • Advanced Analytics and Machine Learning: Exploring opportunities for deeper insights.
  • Security Enhancements: Focused on improving the security posture of the data pipeline.
  • Continuous Monitoring and Optimization: Implementing a robust monitoring system for continuous assessment.


Emphasizes the success of the collaboration, transforming Tervita's data pipeline infrastructure into a scalable, real-time, and efficient system. Stresses the importance of staying abreast of technological advancements for innovation in the smart mobility insights landscape.

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