Sharper operational efficiency
Key challenges
A multi-national retailer sought a migration strategy and roadmap for their cloud journey, aiming to build a next-generation architecture to support their real-time platforms, including their online store.
Migrating and consolidating data
Need for modernization and scalability
Supporting high-traffic, real-time transactions
Building adaptable infrastructure for future growth
The solution
Data integration & replication
Migrated data to GCP
Built sales data pipelines
Integrated ML for insights
Real-time insights
Developed models for insights
Enabled REST APIs
Integrated across platforms
1
Data pipeline setup
Automated data ingestion to GCP
Used GCP tools for fast processing
Ensured real-time sales flow
2
Machine learning models
Developed predictive models
Trained on historical data for trends
Enhanced decisions with analytics
3
API & security
Built REST APIs
Managed flow using Cloud composer
Secured access with Cloud endpoint
Operational efficiency
Support to optimize database partitioning
Helped reduce resource usage
Scalability support
Data-driven insights
Applied ML to customer behavior
Introduced SKU combinations
Support to enhance customer satisfaction
Business growth
Help boost revenue
Help to enhance inventory management
Support to strengthened retail strategy
Enhanced data scalability
Continuous optimization of data infrastructure to support growing transaction volumes
Advanced AI integration
Leveraging machine learning for deeper insights into customer behavior and trends
Seamless multi-platform integration
Expanding the API ecosystem to enhance integration across mobile, web, and in-store applications
