How do I interpret precision and scale of a number in a database?

sql

decimal-precision

data-type-selection

sql-server-rounding

byAlex Kataev·Feb 12, 2025

Precision is the max count of digits in a number, while scale is the decimal fraction. A DECIMAL(5,2) allows for a value like 123.45: 5 digits total (precision), with 2 after the decimal (scale).

To ensure accuracy in your SQL numeric data types such as DECIMAL and NUMERIC, always specify both precision and scale. This choice dictates the max magnitude and granularity of number you can store.

Consequences of undermining precision and scale

Not respecting the limits of precision and scale can lead to truncation or rounding errors. For instance, an attempt to store 1234.567 in a DECIMAL(5,2) column will yield 1234.57, which might lead to unexpected data loss. So, always ensure that the precision and scale of your database columns match with the requirements of your data.

Selecting the right numeric data type

Proper data handling requires careful selection between DECIMAL or FLOAT. DECIMAL is ideal for exact values, while FLOAT or REAL is suitable for approximations. Although using FLOAT saves storage space and improves computation time, it's not suitable for financial or sensitive computations due to the possibility of rounding errors.

SQL Server and its rounding shenanigans

In SQL Server, input values halfway between two rounded values are rounded to the nearest even number - a practice known as banker's rounding. #TIL finance folks are more unbiased than computers 😄, it's good to understand this behavior for critical data interpretation.

Handling Decimal overflow

An Arithmetic overflow error is raised when a number exceeds the declared precision limits. To avoid your application 'exploding', contemplating using a larger precision, or opting for a different data type might be a good strategy. #BecauseNobodyLikesABoom 😁

Practical examples and uncanny scenarios

Examples of practical use-cases:

Numeric data in accounting systems: They often require high precision in decimal values.
Scientific measurements and computations: They might favor FLOAT data type for efficiency over precision.
Currency conversions: The precision and scale become essential to avoid leakages during transactions.

Some peculiarities to account for:

A DECIMAL(5,2) would store 123.999 as 124.00, showcasing rounding in operation.
A DECIMAL(5,-2) means values are rounded to nearest hundred (before the decimal); like 12345 inserted becomes 12300.
Trying to input a non-numeric value into a decimal column results in an error, so always run data validations/pre-processing.

Key takeaways for developers

Ensure your column specifications align with the nature of your data and requirements.
Understand how different SQL engines handle rounding and precision.
Be aware of boundary conditions to prevent overflow or truncation.
Consider performance and storage trade-offs when choosing between FLOAT and DECIMAL.