Chapter 6 – Database Normalization and Data Warehousing by Rahim Zulfiqar Ali - CAF 3 - CA ICAP 2025

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Database Normalization
Purpose:
✅ Eliminate redundancy (duplicate data)
✅ Improve data integrity (accuracy & consistency)
✅ Simplify updates and maintenance

Main Normal Forms:
1️⃣ 1NF (First Normal Form) –
No repeating groups or arrays.
Each field holds atomic (indivisible) values.
Every row is uniquely identified (Primary Key).

2️⃣ 2NF (Second Normal Form) –
Must be in 1NF.
No partial dependency — non-key attributes depend on the whole primary key.
3️⃣ 3NF (Third Normal Form) –

Must be in 2NF.
No transitive dependency — non-key attributes should not depend on other non-key attributes.
💡 Example: Employee → Department → Department Head → avoid repeating department info for each employee.

💻 OLTP (Online Transaction Processing)
Real-time, operational systems handling day-to-day transactions.
Examples: SAP, Oracle ERP, QuickBooks.
Used for:
Recording invoices
Payments
Inventory updates
🧾 CAs use OLTP to ensure accurate daily entries.

📈 OLAP (Online Analytical Processing)
Analytical systems for reporting and decision-making.
Data comes from OLTP and is summarized for insights.
Tools: Power BI, Tableau, Excel Pivot Tables.
📊 Used for:
Sales analysis
Profit margins
Budget vs. actuals
🎯 CAs use OLAP for financial analysis and business consulting.

🗃️ Data Warehousing & ETL
Data Warehouse: A centralized repository combining multiple data sources for analysis.
ETL (Extract, Transform, Load):
Extract data from various sources
Transform it into consistent formats
Load into data warehouse
⚙️ Common Tool: Power Query (Excel & Power BI)

🔑 Keys & Relationships
Primary Key: Unique identifier for each record
Foreign Key: Connects related tables
Relationship ensures data consistency and avoids duplicates.

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