Water is an essential yet limited resource whose management is increasingly challenging due to urban growth, climate variability, and limited infrastructure, especially in developing countries. In Côte d’Ivoire, the national water utility SODECI oversees production, distribution, and consumption monitoring, but faces significant obstacles. These include reliance on manual meter readings, delayed or inaccurate data from smart meters, and the absence of real-time alerts. As a result, both utilities and consumers struggle with unreliable consumption data, leading to billing inaccuracies, undetected leaks, mistrust, and inefficient planning. Many water utilities in Sub-Saharan Africa operate with fragmented, low-digital systems and lack structured, continuous data needed for effective analysis. They have limited tools for understanding historical trends, identifying anomalies, or forecasting demand. Existing systems focus primarily on billing rather than data-driven monitoring or prediction. To address these gaps, the paper proposes a new system aimed at improving water consumption monitoring and understanding for both consumers and utilities in Côte d’Ivoire. The system integrates data collection, analysis, and visualization to enhance transparency and decision-making. It provides insights tailored to different stakeholders and supports proactive management of water use. The paper proposes a suitable and predictable water consumption data model that captures abnormal events and alerts consumers and producer. Algorithms that cleanse and retrieve the abnormal water consumption from a given data set are proposed too.