Calculating Total Sales Revenue for Specific Salespersons Using SQL

2025-02-09

:
In this article, we will explore a basic yet essential SQL query that calculates the total sales revenue for specific salespersons, namely Samantha and Lisa. This type of query is commonly asked in interviews, even by major companies like Amazon and Salesforce. We will walk through the schema, dataset, and the query itself, providing a detailed explanation along with practical SQL commands.

Schema and Dataset:

First, let’s create the `sales_performance` table and insert the provided dataset:

CREATE TABLE sales_performance (
salesperson VARCHAR(50),
widget_sales INT,
sales_revenue INT,
id INT PRIMARY KEY
);

INSERT INTO sales_performance (salesperson, widget_sales, sales_revenue, id) 
VALUES 
('Jim', 810, 40500, 1),
('Bobby', 661, 33050, 2),
('Samantha', 1006, 50300, 3),
('Taylor', 984, 49200, 4),
('Tom', 403, 20150, 5),
('Pat', 715, 35750, 6),
('Lisa', 1247, 62350, 7);

SQL Query:

The goal is to calculate the total sales revenue for Samantha and Lisa. Here’s the SQL query to achieve this:

SELECT SUM(sales_revenue) AS total_revenue
FROM sales_performance
WHERE salesperson IN ('Samantha', 'Lisa');

Explanation:

1. SELECT SUM(sales_revenue) AS total_revenue: This part of the query calculates the sum of the `sales_revenue` column and labels the result as total_revenue.
2. FROM sales_performance: Specifies the table from which to retrieve the data.
3. WHERE salesperson IN (‘Samantha’, ‘Lisa’): Filters the rows to include only those where the `salesperson` is either Samantha or Lisa.

Expected Output:

The query will return the total sales revenue generated by Samantha and Lisa combined. In this case, the output should be:

total_revenue
112650

What Undercode Say:

In the realm of cybersecurity and IT, mastering SQL is crucial for data analysis, database management, and even security auditing. SQL is often used to query logs, analyze user activities, and detect anomalies. Here are some additional Linux and SQL commands that can be useful in a cybersecurity context:

1. Linux Commands:

• grep: Search through logs for specific patterns.

  grep "failed login" /var/log/auth.log
  

• awk: Process and analyze text files, such as logs.

  awk '{print $1}' /var/log/nginx/access.log | sort | uniq -c | sort -nr
  

• netstat: Monitor network connections.

  netstat -tuln
  

2. SQL Commands:

• User Activity Monitoring:

  SELECT * FROM user_activity_log WHERE activity_type = 'login' AND timestamp > NOW() - INTERVAL '1 day';
  

• Detecting Unusual Login Patterns:

  SELECT user_id, COUNT(<em>) AS login_attempts
  FROM login_attempts
  WHERE timestamp > NOW() - INTERVAL '1 hour'
  GROUP BY user_id
  HAVING COUNT(</em>) > 5;
  

• Database Backup:

  mysqldump -u username -p database_name > backup.sql
  

3. Cybersecurity Tools:

• Nmap: Network scanning tool.

  nmap -sP 192.168.1.0/24
  

• Wireshark: Network protocol analyzer.

  wireshark
  

4. URLs for Further Reading:

• SQL Injection Prevention
• Linux Command Line for Beginners
• Cybersecurity Best Practices

Conclusion:

Understanding and practicing SQL queries like the one demonstrated in this article is fundamental for anyone in the IT or cybersecurity field. These skills are not only essential for data analysis but also for securing databases and monitoring user activities. By combining SQL with Linux commands, you can create powerful scripts and tools to enhance your cybersecurity posture. Keep practicing and exploring new commands to stay ahead in the ever-evolving world of technology.

References:

Hackers Feeds, Undercode AI