Analyzing snowfall data and developing predictive models for cost-effective snow removal is critical for local governments, especially those in snow-prone regions. This guided project leverages the History on Demand Direct API in IBM Environmental Intelligence to empower you with the ability to access and analyze historical weather data. By correlating snowfall data with maintenance costs, you'll enhance your skills in budget planning and resource management. This project is not only an opportunity to delve into data-driven decision-making but also a chance to make a tangible impact on the efficiency and strategic planning of snow removal operations. Whether you are an aspiring data analyst, a local government official, or simply interested in the intersection of weather data and public resource management, this project is a valuable addition to your skillset.


Note: To complete this project, you must register to receive free access to the IBM Environmental Intelligence API keys. The process is simple and steps are provided in the project.


What You'll Learn

After completing this project, you will be able to:
- Access and extract historical weather data using the History on Demand Direct API.
- Correlate snowfall data with maintenance costs to identify trends and insights.
- Develop predictive models for budget planning and resource allocation in snow removal.
- Enhance your data-driven decision-making skills for efficient management of public resources.



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 What You'll Need

Before starting this guided project, ensure that you have:
- Basic knowledge of data analysis and statistics.
- Familiarity with Python programming language.
- Access to a modern web browser like Chrome, Edge, Firefox, Internet Explorer, or Safari.