This project demonstrates a real-world ETL pipeline built with SQL Server Integration Services (SSIS) to process bank card transactions from multiple acceptance channels such as ATM, POS, Internet, and more. The goal is to load clean and structured data into a SQL Server Data Warehouse for downstream analysis and reporting.
Banks and financial institutions receive millions of daily transactions from various channels. This solution gathers and processes these transactions from TRC and SHP files, stages them, and loads them into a structured Fact table for accurate analytics and dashboarding.
| # | Package Name | Description |
|---|---|---|
| 1 | 1_Staging_Load_From_TRC_Files.dtsx |
Imports raw transaction data from TRC files into the staging layer. |
| 2 | 2_Fact_Load_From_TRC_Staging.dtsx |
Processes data from TRC staging and loads it into the Fact table. |
| 3 | 3_Staging_Load_From_SHP_Files.dtsx |
Imports raw transaction data from SHP files into the staging layer. |
| 4 | 4_Fact_Load_From_SHP_Staging.dtsx |
Processes data from SHP staging and loads it into the Fact table. |
- SQL Server Integration Services (SSIS)
- SQL Server / Data Warehouse
- Flat file / TRC & SHP parsing
- Visual Studio SSIS Projects
- Data Flow Tasks & Conditional Splits
- Raw Input: TRC / SHP transaction files from payment switch
- Staging Load: Parse and validate into staging tables
- Transformation: Clean, derive, and enrich data
- Fact Load: Insert into fact table with proper keys
- Analyze transaction volumes by channel (ATM, POS, Internet)
- Track trends across time and geography
- Measure terminal/device performance
- Support fraud detection and risk analysis
✅ Ready for deployment and demo
💡 Ideal for recruiters, employers, or LinkedIn portfolio posts
Ali Parva
💼 Data Engineer | Expert in ETL, SSIS, Azure Data Factory
🌍 LinkedIn | GitHub
This project is for demonstration and learning purposes.