Real-Time Clickstream Analytics for Smarter Talent Acquisition

Our client, a prominent firm in the job placement sector, needed to gain a deep, precise understanding of how job seekers interacted with their platform. Their systems generated millions of clickstream events daily—capturing user visits, specific job views, and navigation paths.

However, this data was massive, highly unstructured, and lacked a central processing pipeline. The sheer volume and velocity made it impossible to analyze manually or with traditional databases. The business was flying blind, unable to use this rich behavioral data to optimize job advertisement placement or improve content relevance in a timely manner.

DataClarity designed and implemented a modern, scalable Real-Time Analytics Platform leveraging the power of AWS and Databricks. The goal was to transform raw, high-volume streams into reliable metrics instantly.

• Real-Time Ingestion: We utilized Amazon Kinesis to capture and buffer massive streams of raw clickstream events with low latency.
• Lakehouse Processing: Data was routed to a Databricks Lakehouse platform. Using Spark Structured Streaming, we processed the unstructured data on the fly, cleaning, enriching, and structuring it into a "Silver" layer for analysis.
• Scalable Storage: All data was securely stored in AWS S3 (Data Lake), providing a cost-effective and infinitely scalable foundation.
• Serving Layer: Aggregated metrics were served via high-performance APIs and BI dashboards, allowing product and marketing teams to see user behavior as it happened.