"Sales Insights using MySQL and Tableau" is a powerful and data-driven solution designed to provide comprehensive and actionable sales analytics for businesses. By leveraging the capabilities of MySQL, a reliable and efficient relational database management system, and Tableau, a leading data visualization platform, this solution enables organizations to gain valuable insights into their sales performance.
Sales director wants to know the performance of the company in various Indian states & accordingly provide some discount.
Q1. Revenue breakdown by cities.
Q2. Revenue brekdown by years & months.
Q3. Top 5 customers by revenue & sales quantity.
Q4. Top 5 Products by revenue.
Q5. Net Profit & Profit Margin by Market
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Show all customer records
SELECT * FROM customers;
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Show total number of customers
SELECT count(*) FROM customers;
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Show transactions for Chennai market (market code for chennai is Mark001
SELECT * FROM transactions where market_code='Mark001';
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Show distrinct product codes that were sold in chennai
SELECT distinct product_code FROM transactions where market_code='Mark001';
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Show transactions where currency is US dollars
SELECT * from transactions where currency="USD"
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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;
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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";
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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");
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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";