SQL stands for Structured Query Language. It is used to store, manipulate, and retrieve data present in a database server. We use the DISTINCT keyword in SQL with a SELECT statement to remove the duplicate records and return unique records. In this article, we will explore and understand the DISTINCT keyword. 

The DISTINCT keyword in SQL is a powerful tool for keeping your data tidy and focused. Want to avoid seeing the same record twice? DISTINCT is your answer.

The Power of Uniqueness:

• Removes Duplicates: When used with the SELECT statement, DISTINCT filters out duplicate rows based on the specified columns. Imagine a customer table with multiple entries for the same person. Using DISTINCT on the customer_name column ensures you only see unique customers.
• Counts Uniques: The COUNT function combined with DISTINCT returns the count of unique values in a column. Need to know how many different countries your customers come from? Use COUNT(DISTINCT country).
• Multiple Columns: You can specify multiple columns in the DISTINCT clause. This ensures only rows with unique combinations of those columns appear. Find all cities with distinct combinations of state and population.

But It's Not Magic:

• Performance Impact: Removing duplicates requires comparing rows, which can be resource-intensive, especially on large datasets. Use DISTINCT judiciously, considering alternative methods like grouping and aggregation when possible.
• Hidden Details: DISTINCT by default considers all columns in the SELECT clause for uniqueness. Be mindful of unintended consequences, especially with functions or expressions in your selections.
• Not for Sorting: DISTINCT doesn't guarantee any specific order in the results. If order matters, use ORDER BY separately.

Beyond the Basics:

• Using Subqueries: Sometimes, you might need DISTINCT within a subquery to ensure unique results before joining or manipulating data.
• Combining with Aggregation: DISTINCT can be used with aggregate functions like COUNT, SUM, and AVG to get unique summaries based on specific criteria.

Remember:

• Use DISTINCT when you absolutely need unique data.
• Consider performance implications, especially on large datasets.
• Understand how multiple columns and functions interact with DISTINCT.
• Explore alternative methods like grouping and aggregation when suitable.

With these insights, you can harness the power of DISTINCT to keep your SQL queries clean, efficient, and focused on the unique information you need.