The Real-Time User Engagement and Analytics project is designed to build a scalable pipeline that can ingest, process, store, and visualize social media interaction data in near real-time. It focuses on three main data streams:
- Community interactions
- Live streaming events
- Video interactions
This project aims to enable stakeholders to monitor user engagement, platform performance, and behavioral trends effectively.
- Deliver real-time insights into user engagement across social media platforms.
Analyze key metrics to inform content strategies and enhance user experience:
- Community Engagement: Track interactions within communities.
- Live Streaming Metrics: Monitor real-time performance during live events.
- Video Interaction Patterns: Understand user behavior and preferences.
The project leverages the following tools and technologies:
- Apache Kafka: For real-time data ingestion and streaming.
- Apache Spark: For real-time data processing.
- AWS S3: For scalable and durable data storage.
- Snowflake: For efficient querying and data warehousing.
- Metabase: For building interactive dashboards and visualizing analytics.
- Interactive dashboards providing sub-minute latency for engagement metrics.
- Real-time monitoring capabilities to enhance decision-making for content strategies and user experience improvements.