We built a scalable, secure data engineering solution for a leading quick service restaurant chain, enabling real-time analytics, stronger data reliability, improved operational visibility, and better business intelligence access.
Challenge
Our client, a major Quick Service Restaurant (QSR) chain, required a scalable, secure data engineering solution to support real-time analytics and reporting. The challenge involved processing large-scale data (up to 106 terabytes) from various applications, both in batch and near real-time, to make it accessible for business intelligence and customer insights. Ensuring data reliability, fault tolerance, and robust security against cyber threats was critical.
Approach
We developed end-to-end data pipelines leveraging AWS tools like Kinesis, SNS, SQS, Lambda, and Airflow to handle both real-time and batch data processing. We introduced Kafka, Redpanda and Flink for event-driven data sharing, enabling data enhancement on the fly. Datadog and OpsGenie were used for continuous monitoring, with dashboards providing a real-time view of pipeline health. Secure backup and encryption protocols were established to protect data integrity and enable rapid recovery.
Value Delivered
The solution ensured reliable, secure access to critical data for analytics, reduced downtime through proactive monitoring, and enhanced real-time insights into business operations. Our design supported scalability and resilience, enabling the client to make informed, data-driven decisions while protecting against security risks.
