# What Is Float Data Type in Teradata?

//

Angela Bailey

The Float Data Type in Teradata is used to store floating-point numeric values. It is a versatile data type that can represent both small and large decimal numbers with precision.

## Why Use Float Data Type?

The Float data type is useful when you need to store numbers with decimal places and a wide range of values. It provides flexibility in handling scientific calculations, financial data, and other situations where precision is required.

## Float Data Type Syntax

In Teradata, the syntax for declaring a column with the float data type is as follows:

```CREATE TABLE table_name (
column_name FLOAT
);
```

## Precision and Range

Teradata supports different levels of precision for the float data type based on your requirements. The precision determines the number of significant digits that can be stored.

• Single Precision: The single-precision float can store decimal numbers with 7 significant digits.

It uses 4 bytes of storage.

• Double Precision: The double-precision float provides higher precision and can store decimal numbers with 15 significant digits. It uses 8 bytes of storage.

### Note:

The choice between single or double precision depends on the specific needs of your application. If you require higher accuracy, it is recommended to use double precision.

## Examples

### Example 1: Single Precision Float

```CREATE TABLE sales (
amount FLOAT(7)
);
```

In this example, we create a table called ‘sales’ with a column named ‘amount’ using single-precision float data type. The ‘amount’ column can store decimal numbers with up to 7 significant digits.

### Example 2: Double Precision Float

```CREATE TABLE financial_data (
balance FLOAT(15)
);
```

In this example, we create a table called ‘financial_data’ with a column named ‘balance’ using double-precision float data type. The ‘balance’ column can store decimal numbers with up to 15 significant digits.

## Conclusion

The float data type in Teradata is a powerful tool for handling decimal numbers with precision. By choosing the appropriate precision level, you can ensure accurate storage and manipulation of your numeric data.