SSIS Project: Customer Master Data Clean-Up 🧹💡 #studyvlog #youtubeshorts #shorts

💡 SSIS Project: Customer Master Data Clean-Up – End-to-End Demo! 🧹

Managing messy customer data? In this detailed SSIS project walk-through, we’ll show you how to build a complete ETL process to clean, standardize, and validate customer master data using SQL Server Integration Services (SSIS). From identifying duplicates to handling nulls and enforcing data quality rules — this guide has you covered!

🔹 What You’ll Learn & How to Achieve It:

🧩 1. Project Overview & Use Case
✅ Real-world scenario of handling inconsistent customer data
✅ Common issues: duplicates, missing fields, formatting inconsistencies
✅ Goals of the clean-up process: consistency, accuracy, and readiness for reporting or analytics

🛠️ 2. SSIS Package Design
✅ Data Flow setup from raw source to cleaned destination
✅ Apply Derived Columns and Conditional Splits to handle logic
✅ Normalize data: uppercase names, format phone numbers, validate email formats

🧼 3. Data Quality Checks & Transformation
✅ Remove duplicates using Sort + Remove Duplicates
✅ Use Lookup Tasks to validate against existing master tables
✅ Filter invalid or incomplete records for review

🛡️ 4. Error Handling & Logging
✅ Redirect bad records to a quarantine/error table
✅ Implement logging using SSIS built-in log providers
✅ Capture and alert on data issues via email or report

📤 5. Final Load to Master Table
✅ Load only clean and validated data
✅ Use OLE DB Destination for loading into the Customer Master table
✅ Archive raw and rejected data for audit purposes

⏰ 6. Automation & Maintenance
✅ Schedule with SQL Server Agent for daily or weekly runs
✅ Make the package dynamic using variables and expressions
✅ Track data quality over time using custom metrics

📌 This project is a great example of how SSIS can help solve real-world business problems with practical ETL strategies. Ideal for Data Engineers, BI Developers, or anyone working with Customer Data Management (CDM).

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