Data EngineeringStream ProcessingCloud Architecture

Real-Time Analytics Dashboard

Built a real-time analytics pipeline processing 10M+ events per day using Kafka, Spark Streaming, and Snowflake.

Client: FinTech Startup

Results

Reduced data latency from 24 hours to under 60 seconds. Enabled real-time fraud detection saving $2M annually.

Real-Time Analytics Dashboard

Challenge

The client needed to move from batch processing to real-time analytics to power their fraud detection system.

Solution

We designed and implemented a streaming data architecture using Apache Kafka for event ingestion, Spark Structured Streaming for transformation, and Snowflake as the serving layer.

Impact

  • 10M+ events processed daily
  • <60 second data latency (down from 24 hours)
  • $2M annual savings from real-time fraud detection