Addressing Real-Time Data Access Challenges
For Oldcastle, maintaining real-time access to data was critical as they transitioned from an on-premises environment to Infor Cloud ERP. Their legacy systems supported hundreds of complex reports, but the cloud ERP's native reporting capabilities were insufficient for operational needs. The company needed a solution that could replicate their existing reporting infrastructure while leveraging the benefits of the cloud. To achieve this, they integrated Infor with Amazon Aurora, which provided low-latency access to operational data, ensuring uninterrupted reporting for hundreds of users across multiple departments.
Amazon Aurora's scalability and performance allowed Oldcastle to manage the high volume of transactions generated by their business. This ensured that even under heavy workloads, such as peak operational hours, the analytics system maintained its responsiveness. By adopting Aurora, Oldcastle successfully bridged the gap between legacy and cloud-native systems without sacrificing reporting speed.
Handling Complex Reporting Requirements
Oldcastles operations required multidimensional analysis across various domains, including customer service, finance, logistics, and manufacturing. Infor Cloud ERPs basic reporting tools were unable to meet these requirements. By integrating Amazon QuickSight, the company deployed customizable dashboards that could handle these complexities.
QuickSight empowered business users by providing them with intuitive tools to visualize data in real time. This eliminated the need for switching between multiple systems, which was a pain point in their previous workflows. With QuickSight, Oldcastle built a centralized platform where users could access tailored insights without technical expertise.
Enhancing Advanced Analytics Capabilities
To support advanced analytics, Oldcastle leveraged machine learning capabilities within AWS. Real-time demand forecasting and intelligent search features were integrated into their analytics pipeline. These ML-driven features helped optimize inventory management and improve decision-making processes across the organization.
The integration of AI-driven analytics into the existing reporting framework enabled Oldcastle to go beyond descriptive analytics. The adoption of predictive modeling provided actionable insights, enhancing their ability to respond to market demands dynamically.
Scaling for High-Volume Operations
Scalability was a key requirement for Oldcastles analytics solution. With over 100 concurrent users and millions of transactions to process, the system needed to deliver consistent performance. Amazon Auroras ability to scale both storage and compute resources independently ensured that the system could grow alongside the business.
This scalability was complemented by QuickSights serverless architecture, which allowed it to handle fluctuating workloads without manual intervention. By combining these AWS services, Oldcastle created a resilient and scalable system that met their operational demands efficiently.
API-Driven Data Accessibility
Another critical requirement for Oldcastle was the ability to expose data through APIs for secure and efficient access. By utilizing AWS API Gateway, the company enabled seamless data integration with both internal and external applications. This ensured that data could be consumed by various tools and teams without compromising security.
The API-based architecture also facilitated the automation of workflows, reducing operational overhead. By providing flexible and secure data access, Oldcastle improved collaboration across departments and enhanced their ability to respond to changing business needs.