Must-Learn SQL Functions Before Your Next Job Interview

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Structured Query Language (SQL) is a cornerstone skill for data analysts, database administrators, software engineers, and anyone working with data. A strong command of SQL functions can set you apart during interviews, showcasing your ability to manipulate and retrieve data efficiently. In this blog, we will explore the essential SQL functions that you must master to confidently ace your job interviews.

Why Learning SQL Functions is Crucial

SQL functions are pre-defined operations that simplify complex data manipulation tasks. They enable you to perform calculations, transform data, and extract meaningful insights from databases with minimal code. Mastering these functions not only enhances your problem-solving abilities but also demonstrates to potential employers that you can handle real-world data challenges effectively.

Whether you're applying for a role as a data analyst, data engineer, or software developer, being proficient in SQL functions is a non-negotiable skill.

1. Aggregate Functions

Aggregate functions are essential for summarizing data. These functions help you perform calculations across multiple rows, enabling you to generate summaries and insights quickly.

Key Aggregate Functions:
  • COUNT(): This function counts the number of rows that match a specified condition. For example: SELECT COUNT(*) FROM employees WHERE department = 'Sales';. This query returns the total number of employees in the Sales department.
  • SUM(): The SUM function calculates the total of a numeric column. Example: SELECT SUM(salary) FROM employees WHERE department = 'Finance';
  • AVG(): Use this function to find the average value of a column: SELECT AVG(salary) FROM employees;
  • MAX() and MIN(): These functions retrieve the highest and lowest values in a column, respectively. Example: SELECT MAX(salary), MIN(salary) FROM employees;
2. String Functions

String functions are invaluable for text manipulation, a common requirement in data cleaning and reporting tasks.

Key String Functions:
  • CONCAT(): Combines two or more strings into one. SELECT CONCAT(first_name, ' ', last_name) AS full_name FROM employees;
  • SUBSTRING(): Extracts a part of a string based on specified indices. SELECT SUBSTRING(employee_id, 1, 3) FROM employees;
  • UPPER() and LOWER(): Converts text to uppercase or lowercase, respectively. SELECT UPPER(first_name), LOWER(last_name) FROM employees;
  • TRIM(): Removes leading and trailing spaces from a string. SELECT TRIM(' Hello World ') AS cleaned_text;
  • LENGTH(): Calculates the number of characters in a string. SELECT LENGTH(first_name) FROM employees;
3. Date and Time Functions

Handling date and time data is a critical aspect of database management. SQL offers robust functions for working with temporal data.

Key Date and Time Functions:
  • NOW(): Retrieves the current date and time. SELECT NOW();
  • DATE(): Extracts the date part of a timestamp. SELECT DATE(order_date) FROM orders;
  • DATEDIFF(): Calculates the difference between two dates. SELECT DATEDIFF(end_date, start_date) FROM projects;
  • YEAR(), MONTH(), DAY(): Extract specific parts of a date. SELECT YEAR(hire_date), MONTH(hire_date), DAY(hire_date) FROM employees;
  • STR_TO_DATE(): Converts a string into a date format. SELECT STR_TO_DATE('2023-12-22', '%Y-%m-%d');
4. Mathematical Functions

Mathematical functions are essential for performing calculations and deriving numerical insights from data.

Key Mathematical Functions:
  • ROUND(): Rounds a numeric value to the nearest specified decimal place. SELECT ROUND(salary, 2) FROM employees;
  • FLOOR() and CEIL(): Returns the largest integer less than or equal to (FLOOR) or the smallest integer greater than or equal to (CEIL) a number. SELECT FLOOR(45.67), CEIL(45.67);
  • ABS(): Returns the absolute value of a number. SELECT ABS(-123) AS absolute_value;
  • POWER(): Raises a number to a specified power. SELECT POWER(2, 3) AS result;
  • MOD(): Calculates the remainder of a division. SELECT MOD(10, 3);
5. Window Functions

Window functions are advanced SQL features that perform calculations across a set of rows related to the current row. These functions are indispensable for analytical tasks.

Key Window Functions:
  • ROW_NUMBER(): Assigns a unique number to each row in a result set. SELECT ROW_NUMBER() OVER (ORDER BY salary DESC) AS rank FROM employees;
  • RANK() and DENSE_RANK(): Provides ranking of rows in a dataset with or without gaps. SELECT RANK() OVER (ORDER BY salary DESC) AS rank FROM employees;
  • NTILE(): Divides rows into a specified number of groups. SELECT NTILE(4) OVER (ORDER BY salary) AS quartile FROM employees;
  • LEAD() and LAG(): Access data from subsequent or preceding rows in the dataset. SELECT employee_id, salary, LAG(salary) OVER (ORDER BY salary) AS previous_salary FROM employees;
6. Conditional Functions

Conditional logic in SQL enables dynamic data manipulation based on specific criteria.

Key Conditional Functions:
  • CASE: Executes conditional statements. SELECT employee_id, CASE WHEN salary > 50000 THEN 'High' ELSE 'Low' END AS salary_category FROM employees;
  • IF(): Evaluates a condition and returns different outputs based on the result. SELECT IF(salary > 50000, 'High', 'Low') AS salary_category FROM employees;
How to Practice and Prepare for Interviews
  • Use Online Platforms: Websites like LeetCode, HackerRank, and SQLZoo offer practical problems tailored to SQL interviews.
  • Work on Real Datasets: Practice writing queries on publicly available datasets to gain hands-on experience.
  • Review Common Scenarios: Understand how these functions apply to business use cases, such as sales analysis, customer segmentation, and trend identification.
  • Mock Interviews: Simulate interview scenarios with a focus on problem-solving and optimization techniques.
Conclusion

SQL functions are the building blocks of effective data analysis and manipulation. By mastering these must-learn functions, you can confidently tackle SQL-based interview questions and demonstrate your technical expertise to potential employers. From aggregate and string functions to advanced window functions, investing time in learning these tools will significantly enhance your data-handling capabilities and career prospects.

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