The purpose of this project is to create a financial data warehouse that can be used to analyze and predict market trends. The data warehouse will be used to store and analyze historical data from various financial markets, including stocks, bonds, and commodities. The data warehouse will be used to create predictive models that can be used to make investment decisions.
The ETL process for this project was relatively straightforward. We used Python to load the data. The data was extracted from a variety of sources, including CSV files and APIs. The data was then transformed and loaded into a our warehouse for further analysis.
For more information on the ETL creation process, please see the ETL documentation.
Checkout our installation documentation here
- S&P 500 Stock Data
- S&P 500 Stock Index Data
- S&P 500 Stock Index Data 2
- Crude Oil Data
- Gold Data
- US 14-Year Bond Historical Data
- Silver Data
- All Other Commodity Data
- VTI DATA
This project is licensed under the MIT License - see the LICENSE.md file for details.