ExcelR Assignment Solution for BA and Data Analytics. SQL #11 Subqueries and their applications

ExcelR Assignment Solution for BA and Data Analytics. SQL #11 Subqueries and their applications



ExcelR Assignment Solution for BA and Data Analytics. SQL Assignment 10) b. LEAD and LAG

ExcelR Assignment Solution for BA and Data Analytics. SQL Assignment 10 Window functions - Rank, dense_rank, lead and lag

Year & Month Wise Orders + YoY % Change using Window Functions | SQL Tutorial for Beginners

OR (catchier)

SQL Window Functions Tutorial | Year-Month Order Count + YoY % | LEAD, LAG, SUM, GROUP BY


a) Using customers and orders tables, rank the customers based on their order frequency

b) Calculate year wise, month name wise count of orders and year over year (YoY) percentage change. Format the YoY values in no decimals and show in % sign.

Table: Orders

Expected output:

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Master SQL Window Functions with this practical and easy explanation!
In this video, we solve a real-time SQL question:

Q10. Using Customers and Orders tables, rank the customers based on their order frequency.
We also learn the difference between RANK, DENSE_RANK, LEAD, and LAG using a step-by-step demo.

Learn how to calculate Year-wise and Month-wise order count along with Year over Year (YoY) % change using SQL Window Functions.
This video is part of Q10 – Window Functions (Rank, Dense_Rank, Lead, Lag, etc.) and is perfect for students preparing for interviews, SQL assignments, data analyst jobs, BI roles, and SQL exams.

✅ In this video you will learn:

How to extract Year and Month Name from a date column

How to calculate Total Orders per Year & Month

How to calculate YoY % Change using LAG() window function

How to format YoY as percentage with no decimals

Use of GROUP BY, Order Aggregation, and Window Functions

Best practices for writing clean SQL Server queries

🎯 Topics Covered:

SQL Window Functions

LAG(), LEAD()

Group By Year and Month

YoY (Year over Year) Formula

Data Analytics SQL Problems

SQL Server (SSMS) Examples

📝 Sample Query Covered in Video:
SELECT
YEAR(orderDate) AS OrderYear,
DATENAME(MONTH, orderDate) AS MonthName,
COUNT(*) AS TotalOrders,
LAG(COUNT(*)) OVER (ORDER BY YEAR(orderDate), MONTH(orderDate)) AS PrevYearOrders,
FORMAT(
(COUNT(*) - LAG(COUNT(*)) OVER (ORDER BY YEAR(orderDate), MONTH(orderDate)))
100.0 / NULLIF(LAG(COUNT(*)) OVER (ORDER BY YEAR(orderDate), MONTH(orderDate)), 0),
'P0'
) AS YoY_Percentage
FROM Orders
GROUP BY YEAR(orderDate), MONTH(orderDate), DATENAME(MONTH, orderDate)
ORDER BY YEAR(orderDate), MONTH(orderDate);

💡 Who should watch this?

SQL Beginners

Data Analyst aspirants

Power BI / Excel / Tableau learners

BCA / MCA / B.Tech students

Anyone preparing for SQL Interviews

🔍 Topics Covered:

What are SQL Window Functions?

How RANK() works in SQL

How DENSE_RANK() is different from RANK()

Using LEAD and LAG for comparing previous and next values

Customer order frequency calculation

Real-time business use case: Ranking customers by number of orders

Complete SQL query explanation

#sql #sqltutorial #windowfunctions #sqlserver #ssms #dataanalytics #sqlinterview #leadlag #groupby #yoy #businessanalytics #learnsql #sqltraining #vikaseduclass


💡 Perfect for:

SQL beginners to advanced learners

Data analysts preparing for interviews

Students learning Window Functions

Anyone working with relational databases


Whether you’re learning MySQL, SQL Server, or PostgreSQL, this video will help you understand how SQL queries actually work — step-by-step!

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🏷️ Tags (SEO Optimized)

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🔥 Hashtags (High Reach)

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