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Client context
ProNatura is a waste management company based in Bydgoszcz, focused on environmentally responsible processing of municipal waste. The organization operates large-scale systems for waste collection and disposal, where accurate scheduling and reliable communication with residents are essential.
The challenge
The waste collection schedule needed to be distributed through both digital and printed channels, making accuracy critical.
However, the source data was inconsistent and partially edited manually, leading to frequent errors in schedules. These inconsistencies created confusion for residents and increased operational complexity.
At the same time, the previous system relied on direct database integration, which lacked validation mechanisms and made it difficult to correct errors automatically.
What it took to deliver results
To improve accuracy and reduce operational issues, the system needed to:
- automatically validate and correct inconsistent input data
- generate reliable schedules for both digital and print channels
- provide flexibility to adjust specific dates when needed
- reduce dependency on manual data correction
- ensure consistency across all communication channels
The goal was to create a system that could transform imperfect input data into reliable and usable output.
The solution
A serverless data processing platform was introduced to manage and correct waste collection schedules. It applies automated correction algorithms to incoming data, identifying and fixing inconsistencies before schedules are generated. It also supports both web-based access and integration with external printing systems, making sure that residents receive accurate information regardless of the communication channel.
By introducing structured validation and correction logic, the platform replaces unreliable direct database integration with a controlled and scalable data processing pipeline.
It was built using cloud-native and web technologies:
- Python for backend processing and data correction logic
- React (SPA) for the user interface
- AWS Cloud for serverless infrastructure
- DynamoDB for data storage
How it works
Incoming data is processed through a set of correction algorithms that detect inconsistencies and adjust values automatically. Where necessary, users can manually update specific dates through the system interface, ensuring flexibility without compromising overall data integrity.
Once validated, the system generates schedules for individual addresses and distributes them across both digital platforms and print workflows. All components are hosted in the cloud, enabling scalable and reliable processing.
Impact on operations
The introduction of automated data correction significantly improved the reliability of waste collection schedules. Teams no longer need to manually fix inconsistencies at scale, reducing workload and minimizing the risk of errors. At the same time, consistent data across channels improved communication with residents.
Business impact
The system delivered measurable improvements across key areas:
- Reduced scheduling errors, through automated data correction
- Improved data consistency, across digital and print channels
- Lower printing costs, through optimized schedule generation
- Reduced manual workload, by eliminating repetitive corrections
- More reliable communication, improving service quality for residents
We’ll review your goals, technical constraints, and opportunities to design a solution that fits your organization.
