Sample Project · Market Intelligence
Stock Market Investment Intelligence Pipeline
An end-to-end analytics platform that collects stock market, company financial, and macroeconomic data; transforms it into investment indicators; stores it in a structured database; and presents market opportunities and risks through interactive Power BI dashboards.
Challenge
Investors often evaluate stocks using information spread across multiple sources, including price history, financial statements, valuation metrics, economic indicators, and market news. Manually combining these datasets is time-consuming, inconsistent, and makes it difficult to compare investments objectively.
Approach
Build an automated data pipeline that:
Extracts stock prices, trading volumes, company fundamentals, and economic indicators from public APIs
Cleans and standardizes the data using Python
Engineers valuation, growth, profitability, momentum, volatility, and risk metrics
Loads the processed data into Azure SQL
Uses Power BI to rank securities and visualize portfolio-level insights
Solution
The pipeline creates a centralized investment-intelligence system that evaluates stocks using indicators such as:
Price-to-earnings ratio
Revenue and earnings growth
Return on equity
Dividend yield
Moving-average trends
Price momentum
Historical volatility
Maximum drawdown
Beta
Risk-adjusted return
Composite investment score
The Power BI dashboard allows users to compare companies, identify potentially undervalued securities, examine risk-return relationships, and drill into individual stock performance.
Impact
The platform reduces manual research, creates a consistent stock-evaluation framework, and enables faster comparisons across securities. It helps investors identify opportunities, understand portfolio risk, and make more evidence-based investment decisions.
System architecture
Stock Market, Macroeconomic, & Financial Statements API
Python ETL
Feature Engineering Layer
Azure SQL Data Storage
Power BI Dashboard
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