Implemented dynamic holiday and event multipliers in sales generation…

src/fabric/datagen/business_growth_logic.py

@@ -61,12 +61,55 @@ def calculate_business_phase(current_date: datetime, start_date: datetime, end_d
 
 def get_market_event_multiplier(current_date: datetime) -> Tuple[str, float, float]:
     """
-    Simple market events - minimal seasonal variation for smooth trends.
+    Calculate market event multipliers based on the date.
+
+    Includes:
+    - Memorial Day Sale (Fri–Mon around last Monday of May): 1.4x frequency, 1.2x size
+    - Black Friday / Cyber Monday (Fri after Thanksgiving through Cyber Monday): 1.8x frequency, 1.3x size
+    - Holiday Rush (Dec 10–24): 1.5x frequency, 1.25x size
+    - Christmas Day (Dec 25): 1.1x frequency, 1.1x size
 
     Returns:
         Tuple[str, float, float]: (event_name, order_frequency_multiplier, order_size_multiplier)
     """
-    # Keep it simple - just normal business operations
+    month = current_date.month
+    day = current_date.day
+    current_date_only = datetime(current_date.year, current_date.month, current_date.day)
+
+    # 1. Memorial Day Weekend (Friday before to Monday of Last Monday in May)
+    if month == 5:
+        # Find last Monday in May
+        memorial_monday_dt = None
+        for d in range(31, 23, -1):
+            dt = datetime(current_date.year, 5, d)
+            if dt.weekday() == 0:  # Monday
+                memorial_monday_dt = dt
+                break
+        if memorial_monday_dt and (memorial_monday_dt - timedelta(days=3)) <= current_date_only <= memorial_monday_dt:
+            return "Memorial Day Sale", 1.4, 1.2
+
+    # 2. Black Friday / Cyber Monday (Friday after Thanksgiving to Cyber Monday)
+    # Thanksgiving is 4th Thursday in November. Cyber Monday can overflow into December.
+    if month == 11 or month == 12:
+        thursdays = []
+        for d in range(1, 31):
+            dt = datetime(current_date.year, 11, d)
+            if dt.weekday() == 3:  # Thursday
+                thursdays.append(dt)
+        thanksgiving_dt = thursdays[3]
+        black_friday_dt = thanksgiving_dt + timedelta(days=1)
+        cyber_monday_dt = thanksgiving_dt + timedelta(days=4)
+
+        if black_friday_dt <= current_date_only <= cyber_monday_dt:
+            return "Black Friday / Cyber Monday", 1.8, 1.3
+
+    # 3. Holiday Rush / Christmas (December 10 to December 24)
+    if month == 12:
+        if 10 <= day <= 24:
+            return "Holiday Rush", 1.5, 1.25
+        elif day == 25:
+            return "Christmas Day", 1.1, 1.1
+
     return "Normal", 1.0, 1.0
 
 def get_customer_tier_multiplier(customer_relationship_type: str, base_multiplier: float) -> float:

src/fabric/datagen/output/sample_sales_data_summary.md

@@ -1,27 +1,27 @@
 # Sales Data Generation Summary
 
-**Generated**: 2026-04-07 14:39:32  
+**Generated**: 2026-06-18 13:00:45  
 **Date Range**: 2025-01-01 to 2026-04-30  
 **Duration**: 485 days
 
 ## 📊 Generation Overview
 
 ### **Total Summary**
-- **Orders**: 19,344
-- **Order Lines**: 53,219
-- **Sales Payments**: 19,344
-- **Invoices**: 19,344
-- **Finance Payments**: 19,344
+- **Orders**: 19,550
+- **Order Lines**: 53,986
+- **Sales Payments**: 19,550
+- **Invoices**: 19,550
+- **Finance Payments**: 19,550
 - **Customer Accounts**: 1,539
-- **Total Sales Value**: $32,651,205.39
+- **Total Sales Value**: $33,253,352.55
 
 ### **Domain Performance**
 
 | Domain | Orders | Total Sales | Avg Order Value |
 |--------|--------|-------------|----------------|
-| 🏕️ Camping | 8,498 | $8,738,526.77 | $1028.30 |
-| 🍳 Kitchen | 9,356 | $21,430,728.20 | $2290.59 |
-| ⛷️ Ski | 1,490 | $2,481,950.42 | $1665.74 |
+| 🏕️ Camping | 8,519 | $8,766,028.32 | $1029.00 |
+| 🍳 Kitchen | 9,573 | $22,155,271.94 | $2314.35 |
+| ⛷️ Ski | 1,458 | $2,332,052.29 | $1599.49 |
 
 
 ## 🎯 Key Metrics
@@ -33,7 +33,7 @@
 - **Financial Completeness**: Full order-to-payment lifecycle with invoicing
 
 ### **Data Volume**
-- **Average Orders per Day**: 39.9
-- **Average Order Value**: $1687.92
+- **Average Orders per Day**: 40.3
+- **Average Order Value**: $1700.94
 - **Order Line Items**: 2.8 items per order average
 - **Customer Coverage**: 1539 accounts across all domains