How to Copy Data From One Column to Another in the Same Table in SQL?

Efficiency in data manipulation is crucial while using Structured Query Language (SQL). To manage a wide range of tasks, including organizing, retrieving, updating, and deleting data, SQL provides a comprehensive set of instructions. Among these, copying data between columns in the same table is a common and practical operation. This technique is often used for data transformation, creating backups, or generating derived columns for analysis.

In this article, we will explore how to copy data from one column to another in the same table using the UPDATE statement. Through examples, we’ll cover its syntax, significance, and practical applications to demonstrate how it can simplify our database management tasks.

Copying Data Within the Same Table

When data is copied from one column to another, the SQL Data Insertion requires that values for each column are updated in the same table with other columns' values. Data transformation, redundancy, and calculation are common uses of this method. Maintaining data integrity, ensuring data consistency, and optimizing the use of data manipulation methods in a database are at the heart of this method.

Syntax

The syntax for copying data from one column to another in SQL involves the UPDATE statement along with the appropriate column names.

UPDATE table_name
SET to_column = from_column;

Key Terms

• table_name: mentions the name of the table containing both columns.
  
• to_column: Represents the column where the data will be copied.
  
• from_column: Denotes the column from which data will be copied.

Examples of Copying Data Within the Same SQL Table

Copying data within the same SQL table enables efficient data management and transformation. The following examples illustrate common scenarios where this technique can be applied for analysis, backup, or calculated fields.

Example 1: Copying First Names to Last Names

Suppose we have a table named students with columns 'first_name' and 'last_name'. We want to copy the first names of students to their corresponding last names.

Before

Query:

 UPDATE students
SET last_name = first_name;

Outut

Explanation:

Here, the 'first_name' column is successfully copied to the 'last_name' column, resulting in both columns containing the same values.

Example 2: Calculating and Storing Discounted Prices

Suppose we have a table named products with columns 'price' and 'discounted_price'. We want to calculate a 10% discount on prices and store the result in the discounted_price column.

Before

Query:

UPDATE products
SET discounted_price = price * 0.9;

Output

Explanation:

In this example, a 10% discount is applied to the 'price' column, and the resulting discounted prices are stored in the 'discounted_price' column. It's useful for pre-calculating discounted prices to optimize query performance or simplify business logic.

Example 3: Copying Scores for Specific Students

Let's consider a scenario where we have a table named students with columns 'math_score' and 'science_score'. Now, suppose we want to copy the math_score of a student with student_id = 101 to their science_score.

Before

Query:

 UPDATE students
SET science_score = math_score
WHERE student_id = 101;

Output

Explanation:

Here, the math score of the student with 'student_id' 101 (85) is copied to their science score. As a result, the 'science_score' column for this student now contains the same value as their 'math_score' (85). The data for other students remains unaffected.

Significance of Copying Data

1. Data Transformation: Useful for reformatting or preparing data without altering the original column.
   
2. Redundancy: Ensures data availability and recovery options during critical operations.
   
3. Analysis and Reporting: Allows you to pre-calculate or derive values to enhance reporting accuracy and performance.

Conclusion

Copying data within the same SQL table is a fundamental operation for managing and manipulating data. Using the UPDATE statement, we can efficiently duplicate, transform, and analyze data while maintaining the integrity and consistency of our database. Always ensure the columns involved have compatible data types to avoid errors during the copying process. This technique is a powerful addition to our SQL toolkit, enabling streamlined workflows and effective database management.