Water & Energy6 weeks
Leveraging Data Optimization to Combat Fraud in the Environmental Sector
Increase the quality of your data and detect anomalies through in-depth, multi-source analysis.
The fight against fraud requires impeccable data quality. Our collaboration as part of the Water Plan illustrates how AI can help data quality and anomaly detection.
Project Details
- Client
- Water & Environment Company
- Duration
- 6 weeks
- Industry
- Water & Energy
Services
Data-driven strategySmart databasesDecision-making interfaces
Case Study
Project Deep Dive
01
The Challenge
The company had to address several critical challenges:
- Enrich your customer database
- Detecting non-compliant uses of water
- Integrate multiple external data sources
02
Our Approach
By combining Data engineering and data quality standards, we have developed:
- An interactive multi-source map
- An intelligent automatic matching system
- Real-time data validation
03
The Results
Our intervention generated:
- A 20% enrichment of the customer base
- Precise identification of non-compliant uses
- A significant improvement in data quality
This achievement demonstrates how the alliance between Data lineage and Data preparation automation can transform the fight against fraud while optimizing data quality.