Solid Waste Management Data-Pipeline

The Solid Waste Management Data Warehouse and Reporting System is designed to collect and analyze data related to the collection and transportation of solid waste across major cities in Brazil. The system aims to provide insightful reports and analysis that can assist the company in making informed decisions and optimizing their waste management operations.

The system collects data from various sources, including:

• Solid waste collection trucks equipped with IoT sensors and GPS devices.

• Operational systems managing waste collection routes, schedules, and assignments.

• External data sources, such as weather data, population density, and waste disposal regulations.

The data model follows a star schema design, enabling efficient querying and analysis. The fact table captures the details of waste collection transactions, while the dimensions include:

• City: Represents the cities where waste collection takes place.

• Truck Type: Classifies the different types of waste collection trucks.

• Station: Identifies the waste collection stations across cities.

1. Data Extraction: Raw data is extracted from the various sources, including IoT sensors, operational systems, and external data sources.

2. Data Transformation: The extracted data is cleansed, validated, and transformed into a suitable format for analysis. This includes data normalization, aggregation, and enrichment.

3. Data Loading: The transformed data is loaded into the data warehouse, specifically into the appropriate staging and production tables in Amazon Redshift.

4. Data Validation: Quality checks and validation processes are performed to ensure the accuracy and integrity of the loaded data.

5. Incremental Updates: The ETL processes are designed to handle incremental updates, allowing the system to capture new data and keep the warehouse up to date.