Building a Better Mechanism for Retail Price Optimization Insights with Cloud-based Data Mesh Architecture

Our customer is a recognized market leader in retail technology solutions. The customer was facing several challenges that hindered the functioning of its retail price optimization software. These challenges included limitations with managed service, specifically with the data integration tool it was using. The tool lacked support for performant ‘high-volume’ data processing, which is crucial for handling large amounts of data (more than 60 GB) in real-time. AgreeYa implemented a robust data mesh architecture using Google Cloud Platform (GCP) services.

Our implementation offered a scalable and efficient solution for the customer’s retail price optimization software. AgreeYa experts leveraged DAG pipelines and CI/CD practices to ensure a streamlined and efficient data workflow, enabling the retail technology giant to stay ahead of the competition and deliver exceptional results to their software users in the retail industry. Download the Case Study to read more.

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