Understanding Computed Values in SELECT Statements

The concept of computed values in a SELECT clause is a vital feature of SQL, and the simple answer to the question at hand is: Yes, the SELECT clause list can definitely include a computed value.

In SQL, a SELECT statement is responsible for fetching data from a database. The SELECT clause specifies the columns that you want to retrieve in the output of a query.

However, it isn't restricted to only column names. A SELECT clause can include expressions, functions, and arithmetic calculations too, effectively providing a way to compute values based on the existing data in the columns. The syntax is as follows:

SELECT column1, column2, expression... FROM table;

The expression in this context could be a straightforward arithmetic calculation or a complex function involving multiple columns and operators.

For instance, consider this example:

SELECT CustomerName, UnitPrice * NumberOfUnits FROM Sale;

This query fetches the 'CustomerName' and a computed value (i.e., total cost of the products sold) for each record in the 'Sale' table. The computed value is achieved by multiplying the 'UnitPrice' by 'NumberOfUnits'.

Computed values are often especially useful for deriving insights from the raw data. Say, you may want to determine the total salary expense for employees in a company or calculate tax amount for multiple products, etc where computed values can come handy.

Now, let's discuss a few best practices:

• It's good to use meaningful aliases for computed columns for better readability. For example:

SELECT CustomerName, UnitPrice * NumberOfUnits AS TotalSale FROM Sale;

• When using complex expressions, it's advisable to use parentheses to ensure the right order of operations.
• Always remember, computed columns are not stored in the physical database. They are calculated on the fly, each time the query is executed.

In conclusion, the ability to use computed values in SELECT statements is a powerful feature in SQL, allowing for greater flexibility and potential insights from your data.