Ralph Lauren’s retail ecosystem integrated multiple high-volume data sources, including RFID systems, True View, and Deep North analytics platforms. These systems continuously generated streaming data related to inventory movement, sales activity, and in-store customer traffic.

However, the existing architecture struggled to process this data at scale.

High-frequency streaming events were being dropped before reaching Amazon Redshift, leading to incomplete reporting and inconsistencies in downstream analytics. The infrastructure was not optimized for sustained real-time ingestion, especially during peak store activity periods.

As a result, reporting delays impacted visibility into inventory accuracy, sales performance, and customer behavior across stores, limiting the ability to make timely operational decisions.

YCOTEK redesigned the streaming ingestion pipeline to ensure reliable, scalable, and lossless real-time data processing.

At the center of the solution was the implementation of Amazon Kinesis Firehose, which buffered streaming events for up to five minutes before writing them into Redshift. This buffering layer stabilized ingestion during spikes in data volume and eliminated the data loss occurring in the previous architecture.

By enabling controlled, high-frequency batch writes into Redshift, YCOTEK ensured that large volumes of streaming data could be processed consistently without overwhelming downstream systems.

The architecture was designed to guarantee complete and accurate data availability for reporting and analytics workloads, supporting real-time operational visibility across Ralph Lauren’s retail network.

YCOTEK built the solution using a cloud-native data architecture powered by:

The combination of streaming, buffering, orchestration, and analytics technologies created a scalable infrastructure capable of supporting real-time retail intelligence across a global store network.

The new streaming infrastructure significantly improved the reliability and quality of retail analytics across the organization.

With the redesigned pipeline:

The solution enabled Ralph Lauren to strengthen operational visibility across hundreds of stores globally, creating a more dependable foundation for inventory management, retail analytics, and in-store decision-making.