Sales-Insights-of-a-Company

A Data Analysis project on Sales insights of a Brick and Mortar Company using MySQL and Power BI.

This Data Analysis Project aims to provide the insights into the sales performance of a Brick and Mortar Company over the past few years. By analysing various aspects of the sales data, we seek to identify trends and gain a deeper understanding of the company's performance.

Data Sources

The primary dataset used for this analysis is the .sql file named db_dump.sql in the dataset folder containing all the details as rows ansd coloumns.

Tools used

• MySQL [Analysing the data]
• Microsoft PowerBI [Cleaning the data (ETL) and making reports and charts]

Data Analysis syntax(s) in MySQL

Show all customer records

SELECT * FROM customers;

Show total number of customers

SELECT count(*) FROM customers;

Show transactions for Chennai market (market code for chennai is Mark001)

SELECT * FROM transactions where market_code='Mark001';

Show distrinct product codes that were sold in chennai

SELECT distinct product_code FROM transactions where market_code='Mark001';

Show transactions where currency is US dollars

SELECT * from transactions where currency="USD"

Show transactions in 2020 join by date table

SELECT transactions.*, date.* FROM transactions INNER JOIN date ON transactions.order_date=date.date where date.year=2020;

Show total revenue in year 2020

SELECT SUM(transactions.sales_amount) FROM transactions INNER JOIN date ON transactions.order_date=date.date where date.year=2020 and transactions.currency="INR\r" or transactions.currency="USD\r";

Show total revenue in year 2020, January Month,

SELECT SUM(transactions.sales_amount) FROM transactions INNER JOIN date ON transactions.order_date=date.date where date.year=2020 and and date.month_name="January" and (transactions.currency="INR\r" or transactions.currency="USD\r");

Show total revenue in year 2020 in Chennai

SELECT SUM(transactions.sales_amount) FROM transactions INNER JOIN date ON transactions.order_date=date.date where date.year=2020 and transactions.market_code="Mark001";

Data Analysis syntax(s) in Power BI

Formula to create norm_amount column

= Table.AddColumn(#"Filtered Rows", "norm_amount", each if [currency] = "USD" or [currency] ="USD#(cr)" then [sales_amount]*75 else [sales_amount], type any)