This project analyzes corporate action events using SQL, Excel, and Power BI. It includes SQL analysis, Excel dashboards, and an interactive Power BI dashboard to explore corporate action data.
This project covers:
- SQL data analysis
- Excel KPI Dashboard
- SQL Dashboard
- Interactive Power BI Dashboard
- Data cleaning using Power Query
- Data modeling
- Data quality checks
| Tool | Purpose |
|---|---|
| MySQL Workbench | SQL Queries |
| Microsoft Excel | KPI Dashboard |
| Power BI | Interactive Dashboard |
| Power Query | Data Cleaning |
| GitHub | Project Documentation |
The dataset contains information about corporate action events including:
- Company Name
- Country
- Sector
- Event Type
- Announcement Date
- Market Cap Category
- Announcement Source
- Event Status
SQL was used to:
- Count companies
- Count countries
- Count sectors
- Count event types
- Create Views
- Perform aggregations
The SQL file is available in:
corporate_actions_queries.sql
The Power BI report contains three pages.
Features:
- Total Events
- Unique Companies
- Top Country
- Top Sector
- Top Event Type
- Monthly Trend
- Market Cap Distribution
- Interactive Filters
Includes:
- Event Details
- Event Type by Country
- Announcement Source Analysis
- Event Status Analysis
- Identifier Type Analysis
Includes:
- Blank Security IDs
- Blank Event Types
- Blank Sources
- Validation Table
- Status Summary
- Power Query
- Data Model
- Relationships
- DAX Measures
- Cards
- Tables
- Matrix
- Bar Charts
- Line Chart
- Slicers
- Total corporate action events: 250
- 15 unique companies analyzed
- Canada recorded the highest number of events.
- Consumer Goods was the top sector.
- Tender Offer and Rights Issue were the most common event types.
corporate-actions-dashboard/
│── README.md
│── LICENSE
│── corporate_actions_queries.sql
│── Corporate Actions KPI Dashboard.xlsx
│── Corporate_Actions_SQL_Dashboard.xlsx
└── screenshots/
├── excel_dashboard.png
├── sql_dashboard.png
├── powerbi_executive_overview.png
├── powerbi_analysis.png
├── powerbi_data_quality.png
├── power_query.png
└── data_model.png
Through this project, I learned:
- SQL querying
- Data cleaning
- Excel dashboards
- Power BI dashboard development
- Power Query transformations
- Data modeling
- DAX measures
- GitHub project documentation
Jyothi Priya Garnepelli