Big Data Analytics Solution For Tracking User Data

Overview

We developed a full-scale cloud application for a government body based in South Asia to track and analyze user data coming from multiple sources. The application focused on determining user sentiments by fetching and analyzing data from social media, video streaming apps, IoT devices, and geolocation sensors. Due to the heavy volume of data traffic, we created multiple gateways for extraction from their respective sources.

Scope of Work

Our client dealt with massive volumes of data (in terabytes) on an everyday basis. They sought our services to develop a SaaS solution that would efficiently handle data coming from multiple sources. There were four main sources of data viz. IoT devices, video cameras, geolocation sensors, and social media platforms. The scope of work required us to develop a scalable integration hub to extract, process, and load data into databases using advanced extract-transform-load (ETL) methodologies.

Tech Stack Used

Spring Boot, Apache Airflow, Apache Spark, PostgreSQL, Apache Superset, Apache NiFi, Apache Kafka, Amazon S3 Bucket, Docker, Elasticsearch, Redis (v5.x).

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