An end-to-end financial analytics and business intelligence platform built with Python, PostgreSQL, Power BI, SEC EDGAR, Alpha Vantage, and FRED.
The project integrates corporate financial statements, equity-market performance, market-risk metrics, and macroeconomic indicators into a single analytical platform.
It demonstrates a complete data workflow from external API extraction through Bronze, Silver, and Gold data layers to PostgreSQL reporting views and an interactive Power BI dashboard.
The Financial Intelligence Platform analyzes five major U.S. technology companies:
- Apple Inc. — AAPL
- Microsoft Corporation — MSFT
- Alphabet Inc. — GOOGL
- Meta Platforms Inc. — META
- Amazon.com Inc. — AMZN
The SPDR S&P 500 ETF Trust — SPY — is included as the market benchmark.
The platform combines four major analytical areas:
- Corporate financial performance
- Financial ratios and growth metrics
- Equity-market performance and risk
- Macroeconomic conditions
A detailed explanation of the business problem, architecture, financial calculations, data model, engineering decisions, and technical challenges is available in the Project Case Study.
The platform was designed to answer questions such as:
- Which companies are growing revenue and earnings most consistently?
- How have profitability and cash-flow margins changed over time?
- How do company balance sheets compare?
- Which stocks generated the strongest five-year performance?
- Which companies delivered the strongest risk-adjusted returns?
- How volatile are the companies relative to the market?
- How severe were their historical drawdowns?
- How correlated are the stocks with the market benchmark?
- How are interest rates, inflation, unemployment, and GDP growth evolving?
- What is the current macroeconomic environment surrounding company performance?
| Layer | Technology |
|---|---|
| Programming | Python |
| Data Manipulation | pandas |
| File Storage | JSON, CSV, Parquet |
| Financial Statements | SEC EDGAR Company Facts API |
| Market Data | Alpha Vantage |
| Macroeconomic Data | Federal Reserve Economic Data — FRED |
| Database | PostgreSQL |
| Database Connectivity | psycopg, SQLAlchemy |
| Business Intelligence | Microsoft Power BI |
| Development Environment | Visual Studio Code |
| Version Control | Git / GitHub |
The platform follows a layered analytical architecture.
flowchart LR
A["SEC EDGAR"] --> D["Bronze"]
B["Alpha Vantage"] --> D
C["FRED"] --> D
D --> E["Silver"]
E --> F["Gold Analytics"]
F --> G["PostgreSQL"]
G --> H["Reporting Views"]
H --> I["Power BI"]
J["Master Pipeline"] --> D
J --> G
J --> K["Health Check"]
K --> L["PASS / FAIL"]
For the detailed architecture and pipeline design, see Architecture Documentation.
The executive dashboard combines company financial performance, market risk and return, peer benchmarking, and the current macroeconomic environment in a single decision-focused view.
The financial analysis page provides deeper visibility into profitability, balance-sheet structure, cash generation, growth, and historical financial ratios.
The market and risk page compares five-year equity performance, volatility, drawdowns, risk-adjusted returns, beta, and benchmark relationships.
The macroeconomic page tracks interest rates, inflation, unemployment, real GDP growth, and business-cycle conditions using FRED data.