The retail distribution cooperative needed to improve its data processing and usage procedures, as they were complex, laborious and slow. The previous system prevented the generation of reports in real time, forcing weekly or monthly reports. The entity was looking for a solution that would allow it to process large volumes of information from more than 40 operational tables in reduced times, and thus achieve more agile and efficient decision making.
A data processing system based on Spark SQL technology was designed and implemented, replacing the previous PL/SQL approach. This solution allowed replicating all the functionality required for financial reporting, optimizing data loading from multiple sources and drastically speeding up processing time.
We optimize retail data processing with Spark SQL, reducing report generation from 7 hours to 30 minutes and enabling more agile and real-time decisions.
- Process acceleration: Reduction of processing time from 7 hours to only 30 minutes.
- Real-time reporting: Possibility of generating daily reports, improving control and decision making.
- Cost reduction: Reduced need for technical and human resources to execute the processes.
- Scalability: A flexible and robust architecture capable of adapting to the future growth of the organization.
