Case Study:
Scalable Data Platform
Transforming brewery operations with enhanced data processing and advanced analytics.
Case Study:
Scalable Data Platform
Transforming brewery operations with enhanced data processing and advanced analytics.
Client Challenge
A global beverage company struggled to process IoT data from 7 breweries, hindering real-time insights and expansion beyond 100 sites.
A data infrastructure with high compute costs and data quality issues undermined the ROI on technology investments, while limited pipeline visibility hindered strategic decision making and process improvement.
The Solution
We implemented a modern cloud-native data architecture that enabled the company to perform advanced analytics and generate real-time insights of their brewing operations.
- Established a centralised data storage system, S3 data lake, with tiered architecture, ensuring a single, reliable source of truth for all brewery data.
- Implemented an efficient transformation layer that optimised workload distribution and task offloading, significantly reducing infrastructure costs.
- Engineered streamlined AWS data pipelines with Kinesis for near real-time data transformation, enabling analytics and machine learning use cases.
- Comprehensive monitoring and analytics with real-time dashboards and alerts, enabling cross-site benchmarking and enhanced operational visibility.
Solution Value
The solution accelerated time-to-market for new brewery integrations, empowered data-driven decision-making across global operations and laid the foundation for scalable machine learning and analytics capabilities.
- 94 Sites deployed across 38 different countries.
- 75% cost reduction achieved saving $7,000 per month.