EDP reduces costs and improves reliability with YData's solutions

Smart meters are crucial for the energy sector's increase of service efficiency - as they allow new service development and build better customer relationships. 
At the heart of EDP smart meters system is data collection. This data is labeled and used as a source of truth for predictive maintenance. EDP invested in improved data quality to optimize smart grid maintenance costs for better predictions. 

The goal was to effectively reduce the number of false positive events to reduce costs regarding smart meters' operations. Understanding the representativeness of failures in the training data was crucial for assessing performance impact.

Download this case study to learn more about:

• The impact of data quality in predictive maintenance
• The benefits delivered by synthetic data generation to mitigate underrepresented labels