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SQL Advance Data Analytics Project by using CTE and Window Functions

SQLQuery-1. Analyze the yearly performance of products by comparing their sales to both the average sales performance of the product and the previous year's sales.

SQLQuery-2. Segment products into cost ranges and count how many products fall into each segment.

SQLQuery-3. Which Categories contribute the most to overall sales?

SQLQuery-4. Group customers into three segments based on their spending behaviours:

          -VIP : Customers with at least 12months of history and spending more than $5000.
          -REGULAR : Customers with at least 12 months of history but spending 5000$ or less
          -NEW : Customers with a lifespan less than 12 months.

and find the total numbers od customers by each group

SQLQuery-5. CUSTOMER REPORT

Purpose: This report consolidates key customer metrics and behaviours.

#Highlights:

1. Gathers essential fields such as names,ages,and transaction details.
2. Segments customers into categories (VIP,Regular,New) and age groups.
3.Aggregates customer-level metrics:
	-total orders
	-total sales
	-total quantity purchased
	-total products
	-lifespan (in months)
4.Calculates valueable KPIs:
	- recency(months since last order)
	-average order value  
	-average monthly spend

SQLQuery-6. PRODUCT REPORT

Purpose: This report consolidates key product metrics and behaviours.

#Highlights:

1. Gathers essential fields such as product name,category,subcategory and cost.
2. Segments products by revenue to identify High-Performers,Midd-Range,or Low-Range
3.Aggregates product-level metrics:
	-total orders
	-total sales
	-total quantity sold
	-total customers (unique)
	-lifespan (in months)
4.Calculates valueable KPIs:
	- recency(months sincelast sale)
	-average order revenue (AOR)
	-average monthly revenue

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