I develop a comprehensive data warehouse solution for a solid waste management company operating across major cities in Brazil. Tasked with optimizing data-driven decision-making processes, I designed and implemented a robust data infrastructure capable of handling vast amounts of information regarding waste collection and recycling activities. Steps Taken: 1. Requirement Analysis 2. Data Modeling 3. Data Loading 4. Query Optimization 5. Materialized Query Tables (MQTs) 6. Dashboard Creation: Use IBM Cognos Analytics to visualize key performance indicators (KPIs) and metrics derived from the data warehouse. Project Goal: The primary objective of this project was to empower the solid waste management company with a data-driven approach to optimize waste collection and recycling operations. By establishing a robust data warehouse infrastructure and implementing advanced analytics capabilities, the project aimed to enable the company to: - Gain actionable insights into waste collection trends and patterns across different cities and truck types. - Enhance resource allocation and scheduling strategies for improved operational efficiency. - Track progress towards sustainability goals and identify opportunities for environmental impact reduction. - Facilitate evidence-based decision-making at various levels of the organization to drive continuous improvement initiatives.