SQL Tutorial: Change NVARCHAR Data to INT

When working with databases, especially those storing user input or imported data, it is common to encounter numeric values stored in string-based formats such as NVARCHAR. Converting these values to numeric types like INT is a frequent requirement for performing arithmetic operations, data analysis, and maintaining type integrity. SQL Server provides several methods to achieve this conversion, and understanding each method helps ensure accuracy, performance, and error handling in your queries.

This guide explores various approaches to convert NVARCHAR to INT in SQL Server. These methods include CAST, CONVERT, TRY_CAST, TRY_CONVERT, and ISNUMERIC in combination with CAST. Each method has its use case, strengths, and limitations depending on the data quality and the desired error handling behavior. This part focuses on the first method, using CAST, and explains it in detail.

Method Using CAST to Convert NVARCHAR to INT

What is CAST in SQL

CAST is a standard SQL function used to convert an expression from one data type to another. It takes two parameters: the value to be converted and the target data type. CAST is used when you are certain that the value can be successfully converted; otherwise, it results in an error if the data is not compatible. For example, attempting to convert a non-numeric string like ‘abc’ to an integer using CAST will raise an error.

CAST is compliant with ANSI SQL standards and is supported by most relational database management systems, including SQL Server, Oracle, MySQL, and PostgreSQL. It is a straightforward and widely-used function in SQL-based data transformations.

Syntax of CAST for Converting NVARCHAR to INT

To convert a column of NVARCHAR type to INT using CAST, you use the following syntax:

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SELECT CAST(column_name AS INT) AS ConvertedValue

FROM table_name;

In this syntax, column_name represents the column containing the NVARCHAR values, and table_name is the name of the table you are querying. The alias ConvertedValue is used to name the output column containing the result of the conversion.

Example Scenario Using CAST

Consider a table named User_Data which contains a column named user_id. This column is of NVARCHAR type and holds mixed data, including both numeric and non-numeric values. Here is an example of the data:

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user_id

123

456

abc

789

To convert this column to INT using CAST, the following query is written:

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SELECT CAST(user_id AS INT) AS ConvertedValue

FROM User_Data;

This query attempts to convert each value in the user_id column from NVARCHAR to INT. For values like ‘123’, ‘456’, and ‘789’, the conversion is successful, and the result is an integer. However, for the value ‘abc’, SQL Server throws an error because it is not a numeric string. CAST does not handle conversion failures gracefully. It will terminate the query with an error message if any of the rows contain incompatible data.

Error Behavior of CAST Function

The primary limitation of the CAST function is its inability to handle non-numeric strings or any values that cannot be directly converted into the target type. For instance, if a column contains strings such as ‘abc’, ’12ab’, or empty strings, attempting to convert them using CAST will result in an error similar to the following:

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Conversion failed when converting the nvarchar value ‘abc’ to data type int.

This behavior is critical to understand when working with large datasets where some rows might contain unexpected or malformed data. Using CAST in such scenarios requires prior data validation or filtering to avoid query failure.

Importance of Data Cleaning Before CAST

To use CAST effectively, it is essential to ensure that all the values in the column being converted are indeed numeric. This often involves cleaning the data or filtering out invalid entries. For example, you can use a WHERE clause in combination with a function like ISNUMERIC (covered in a later section) to exclude non-numeric data before applying the CAST function.

Here is how such a filter might look:

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SELECT CAST(user_id AS INT) AS ConvertedValue

FROM User_Data

WHERE ISNUMERIC(user_id) = 1;

This approach ensures that only rows with numeric values are processed, thereby avoiding runtime errors. However, even ISNUMERIC has limitations and may return true for values that are technically numeric but not suitable for casting to INT, such as decimal numbers or values with special characters like currency symbols.

Best Practices for Using CAST

To use CAST safely and effectively in SQL queries, follow these best practices:

• Ensure the column data is clean and contains only values that can be successfully cast to the target type.
  
• Use ISNUMERIC or similar checks to filter the data when working with unvalidated or user-generated content.
  
• Understand that CAST is strict and does not tolerate conversion errors. It is best used when data quality is guaranteed or when the query includes robust data validation.
  
• Be cautious when using CAST in production environments where a query failure due to invalid data could interrupt workflows or cause data processing pipelines to fail.
  

When to Use CAST Over Other Methods

CAST is appropriate when:

• You are working with clean, validated data.
  
• You prefer using standard SQL functions supported across different database systems.
  
• You do not need graceful handling of conversion errors.
  
• You want a simple and straightforward method without additional features or syntax.
  

In situations where data may be unpredictable or partially formatted, other functions like TRY_CAST or TRY_CONVERT may be more appropriate, as they provide error handling by returning NULL instead of stopping execution.

Using the CONVERT Function to Convert NVARCHAR to INT in SQL

Converting data from one type to another is a common task in SQL programming. The CONVERT function is another method provided by SQL Server for data type transformation. It offers similar functionality to CAST but comes with additional flexibility. This part explores the usage of CONVERT to change NVARCHAR values into INT type values in SQL.

The CONVERT function is frequently used in environments where data transformation must include formatting or when compatibility with older SQL Server systems is required. While it behaves similarly to CAST in many ways, CONVERT supports style formatting options and has been a legacy choice in Microsoft SQL Server environments.

Understanding the CONVERT Function in SQL

The CONVERT function is a SQL Server-specific feature that allows you to change the data type of a given value. Unlike CAST, which follows the ANSI SQL standard, CONVERT includes a third parameter for specifying a style code. This parameter is mainly used for formatting date and time conversions but can be omitted when converting simple types like strings to integers.

Despite not needing the style parameter in most numeric conversions, understanding its structure is useful for broader applications. For converting NVARCHAR to INT, you only need to specify the target type and the source value.

Syntax of CONVERT for NVARCHAR to INT Conversion

The general syntax for using CONVERT to transform NVARCHAR to INT is as follows:

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SELECT CONVERT(INT, column_name) AS ConvertedValue

FROM table_name;

In this syntax:

• INT is the target data type.
  
• column_name is the name of the column you are converting.
  
• ConvertedValue is an alias for the result of the conversion.
  
• table_name is the name of the table that contains the column.
  

This syntax is simple, clear, and efficient for scenarios where data is already clean and contains only numeric values stored in NVARCHAR format.

Example Scenario with the CONVERT Function

Imagine a table named User_Accounts that stores user identification values in a column named user_id. These values are stored as NVARCHAR, but for processing or analysis purposes, you need to work with them as integers.

Here is an example of data stored in the user_id column:

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user_id

123

456

abc

789

Now, apply the CONVERT function to change these string-based IDs into integers:

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SELECT CONVERT(INT, user_id) AS ConvertedValue

FROM User_Accounts;

This query attempts to convert each row in the user_id column into an integer. If the value is a numeric string like ‘123’, the result will be a proper integer. If the value is non-numeric, such as ‘abc’, the conversion will fail and SQL Server will throw an error.

Error Handling and Limitations of CONVERT

Similar to the CAST function, CONVERT does not automatically handle non-numeric values gracefully. If any value in the column is not a valid integer representation, the query will not complete successfully. Instead, it will raise an error and stop execution.

Here is an example of the error message you might see:

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Conversion failed when converting the nvarchar value ‘abc’ to data type int.

This strict behavior requires extra caution when working with data that may include invalid or unexpected content. To avoid errors, you need to filter out the problematic values or clean the data before applying the CONVERT function.

Filtering Non-Numeric Values Before Using CONVERT

To ensure that the query runs without error, you can add a condition using ISNUMERIC to exclude rows with non-numeric strings. For example:

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SELECT CONVERT(INT, user_id) AS ConvertedValue

FROM User_Accounts

WHERE ISNUMERIC(user_id) = 1;

This query will attempt to convert only those rows where the value in user_id passes the ISNUMERIC check. While this provides a basic safeguard, it is important to note that ISNUMERIC is not perfect. It can return true for values that may not be valid integers, such as decimal numbers or symbols like commas and currency indicators.

Despite these limitations, using ISNUMERIC can still help filter out clearly invalid entries like alphabetic strings or mixed content, reducing the chances of a failed conversion.

Practical Use of CONVERT in SQL Projects

The CONVERT function is often used in business environments where data is imported from external sources such as CSV files, Excel spreadsheets, or APIs. In many cases, these external sources may store numeric values as text. When such data is imported into SQL Server, the columns might default to NVARCHAR, especially if there is inconsistency in the formatting of the values.

To perform calculations or join operations involving these columns, you will need to convert the data into numeric types like INT. CONVERT is a useful tool in these cases, especially when backward compatibility with older SQL versions is a concern.

For example, suppose you have imported a list of employee salaries stored as strings. To calculate average salary or total payroll, you must first convert those string values into integers using a reliable method like CONVERT, after ensuring that all values are valid numbers.

When to Use CONVERT Instead of CAST

While both CONVERT and CAST can be used for the same purpose, there are situations where CONVERT is preferred:

• You are working in a SQL Server environment and need to use style formatting with dates.
  
• You want more control over how certain data types are transformed, especially for date/time and monetary values.
  
• You are maintaining legacy systems or scripts that already use CONVERT extensively.
  
• You prefer SQL Server-specific functions that provide extended compatibility and behavior.
  

However, if your goal is simply to convert strings to integers, and you do not require the additional formatting options, both CAST and CONVERT can be used interchangeably with similar outcomes. The choice depends on personal or team preference, as well as specific project requirements.

Handling Non-Compatible Data with TRY_CAST and TRY_CONVERT in SQL

Data in real-world databases is not always clean or predictable. When converting string-based data such as NVARCHAR into numeric formats like INT, you might encounter non-numeric values such as alphabetic strings, mixed alphanumeric codes, or empty fields. Using functions like CAST or CONVERT will result in errors if any value in the column cannot be converted to the target type.

To address this issue and provide a safer way to attempt data conversion without breaking the entire query, SQL Server offers two important functions: TRY_CAST and TRY_CONVERT. These functions are more robust alternatives to CAST and CONVERT. They attempt the conversion and return NULL if the operation fails, instead of throwing a runtime error.

These functions are particularly useful when working with inconsistent or user-generated data and can significantly improve the resilience and stability of your SQL scripts.

Understanding TRY_CAST in SQL Server

TRY_CAST is similar to CAST in syntax and usage but includes built-in error handling. When TRY_CAST encounters a value that cannot be converted to the desired data type, it does not cause the query to fail. Instead, it returns a NULL value for that specific row. This allows the query to continue processing the rest of the data.

TRY_CAST is ideal for use in reporting, data exploration, and staging tables where invalid data should be ignored rather than blocking the execution of the query.

Syntax of TRY_CAST

The general syntax for TRY_CAST is straightforward:

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SELECT TRY_CAST(column_name AS target_data_type) AS alias_name

FROM table_name;

In this syntax, column_name is the source column containing the NVARCHAR data, target_data_type is the destination type such as INT, and alias_name is the name assigned to the output column.

This function attempts to cast each value individually. If the value is valid, the result is a converted value. If not, it results in NULL.

Understanding TRY_CONVERT in SQL Server

TRY_CONVERT offers similar functionality to TRY_CAST but uses the syntax of the CONVERT function. It also includes an optional style parameter, which is useful for date and time formatting but is not needed when converting NVARCHAR to INT.

TRY_CONVERT behaves exactly like TRY_CAST in that it returns NULL for non-convertible values, thus allowing your query to proceed uninterrupted.

Syntax of TRY_CONVERT

The syntax of TRY_CONVERT is:

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SELECT TRY_CONVERT(target_data_type, column_name) AS alias_name

FROM table_name;

As with TRY_CAST, the result is a successful conversion when possible and NULL when it fails.

TRY_CONVERT is preferred if your organization or existing codebase already relies on the CONVERT family of functions, or if you plan to apply style formatting in future enhancements.

Example: TRY_CAST and TRY_CONVERT in Action

Assume you have a table named Student_Records with a column student_id of type NVARCHAR. The values stored in this column include valid numeric strings and some invalid entries.

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student_id

‘101’

‘102’

‘103’

‘ABC’

You want to convert this column to INT for analysis purposes, but without triggering errors caused by invalid values like ‘ABC’.

Using TRY_CAST

Here is the SQL query using TRY_CAST:

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SELECT

    student_id,

    TRY_CAST(student_id AS INT) AS student_id_int

FROM Student_Records;

Using TRY_CONVERT

Here is the equivalent query using TRY_CONVERT:

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SELECT

    student_id,

    TRY_CONVERT(INT, student_id) AS student_id_int

FROM Student_Records;

Expected Output

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student_id    student_id_int

‘101’         101

‘102’         102

‘103’         103

‘ABC’         NULL

In both cases, the invalid value ‘ABC’ is safely handled by returning NULL instead of raising an error. This allows the query to complete successfully and return meaningful results for the valid entries.

Benefits of TRY_CAST and TRY_CONVERT

These two functions provide a safer and more fault-tolerant method for converting data types in SQL Server. Here are some of the benefits they offer:

• Prevent query failure by returning NULL for invalid values.
  
• Ideal for exploratory data analysis where partial results are acceptable.
  
• Useful in large-scale data migrations where mixed-quality data may be present.
  
• Great for reporting queries that should not break due to a few malformed entries.
  
• Can be used to identify bad data by filtering rows where the result is NULL.
  

For example, to find all rows that failed to convert, you can use a query like this:

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SELECT *

FROM Student_Records

WHERE TRY_CAST(student_id AS INT) IS NULL;

This will return only those rows where the conversion to INT failed, helping you identify and fix issues in the source data.

Considerations When Using TRY_CAST and TRY_CONVERT

While these functions provide significant benefits, they also have some limitations and best practices to consider:

• A result of NULL does not distinguish between genuinely missing data and failed conversion. You may need additional logic to identify the exact cause.
  
• They are available only in SQL Server 2012 and later. If your database uses an older version, these functions are not supported.
  
• TRY_CAST and TRY_CONVERT do not improve performance over regular CAST or CONVERT. Their main advantage is error prevention.
  
• You should still validate critical data at the application or ETL level. These functions are a stopgap for better data cleaning practices.
  

Real-World Use Cases

In practical scenarios, TRY_CAST and TRY_CONVERT are useful in many situations:

• When importing data from flat files or spreadsheets where numeric fields may include accidental alphabetic characters.
  
• In dynamic SQL where column values may vary in format due to user inputs.
  
• For generating data summaries or reports where a few missing or incorrect values should not interrupt the entire process.
  
• In data quality checks where rows with NULL output after TRY_CAST are marked for manual review.
  

These functions act as a protective layer, especially during exploratory analysis, automated reports, and legacy data integration projects.

Data Conversion with ISNUMERIC and CAST in SQL

In SQL Server, converting values from NVARCHAR to INT is a routine task in data transformation workflows. However, not all string values can be directly converted to integers. In cases where invalid or non-numeric data exists, attempting a direct conversion using CAST or CONVERT will result in an error.

To address this challenge without relying solely on error-handling functions like TRY_CAST, SQL Server provides the ISNUMERIC function. This function can be used to filter out non-numeric values before conversion, making your data processing cleaner and more reliable.

Combining ISNUMERIC with CAST allows you to prequalify the data and only attempt conversions on values that are likely to succeed. This approach is especially useful in stored procedures, views, and ETL operations where performance and clarity matter.

Understanding the ISNUMERIC Function

The ISNUMERIC function is used to test whether a value can be interpreted as numeric. It returns 1 if the input can be evaluated as a number and 0 if it cannot. This function works with a wide range of numeric formats, including integers, decimals, currency symbols, and scientific notation.

Although ISNUMERIC is not perfect and can sometimes return true for values that are not valid integers, it serves as a useful preliminary filter to reduce the risk of conversion errors.

Syntax of ISNUMERIC

Here is the basic syntax:

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SELECT ISNUMERIC(column_name) AS IsNumericResult

FROM table_name;

This statement returns 1 for rows that are considered numeric and 0 for non-numeric entries.

Combining ISNUMERIC with CAST for Safe Conversion

To safely convert only the valid numeric values in an NVARCHAR column, you can use ISNUMERIC in the WHERE clause of your SQL query. This way, only rows with numeric content will be included in the result, and the CAST operation will apply only to those.

Syntax Example

Here is the syntax for combining ISNUMERIC with CAST:

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SELECT 

    column_name,

    CAST(column_name AS INT) AS ConvertedValue

FROM table_name

WHERE ISNUMERIC(column_name) = 1;

This query filters the rows using ISNUMERIC and then casts the values to integers. The rest of the rows, which may contain alphabetic or mixed characters, are excluded from the result.

Practical Example with Sample Data

Suppose you have a table named Employee_Records with a column employee_id of type NVARCHAR. The data stored in this column includes the following entries:

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employee_id

‘1001’

‘1002’

‘XYZ’

‘1003’

‘$200’

‘ ‘

‘1E3’

Now you want to extract only the rows where the employee_id can be safely converted to INT.

Query Using ISNUMERIC and CAST

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SELECT 

    employee_id,

    CAST(employee_id AS INT) AS employee_id_int

FROM Employee_Records

WHERE ISNUMERIC(employee_id) = 1;

Expected Output

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employee_id    employee_id_int

‘1001’         1001

‘1002’         1002

‘1003’         1003

‘1E3’          1000

This query excludes rows like ‘XYZ’, ‘$200’, and a blank space because they do not qualify as numeric values. Note that ‘1E3’ is interpreted as scientific notation and is successfully converted to 1000, even though it might not look like a typical integer to a human reader.

Limitations of ISNUMERIC

While ISNUMERIC is helpful, it has some limitations that must be understood to avoid unexpected behavior.

• ISNUMERIC returns true for values that may not be valid integers, such as:
  
  • Scientific notation (e.g., ‘1E4’)
    
  • Currency symbols (e.g., ‘$500’)
    
  • Decimal points (e.g., ‘10.5’)
    
  • Plus and minus signs (e.g., ‘+20’, ‘-30’)
    
• These values can pass the ISNUMERIC check but may still fail or produce unexpected results when cast to INT.
  

Because of these issues, ISNUMERIC should be used with caution when your goal is to extract only whole integers. For stricter validation, you can consider additional logic using LIKE, PATINDEX, or even regular expressions in more advanced SQL environments.

Improving Accuracy with Pattern Matching

To filter values that are strictly digits, you can add additional conditions to the WHERE clause. For example:

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SELECT 

    employee_id,

    CAST(employee_id AS INT) AS employee_id_int

FROM Employee_Records

WHERE ISNUMERIC(employee_id) = 1

AND employee_id NOT LIKE ‘%[^0-9]%’;

This query ensures that only values made entirely of digits are converted, filtering out values like ‘$200’ or ‘1E3’. The LIKE condition uses a negated character set ([^0-9]) to exclude any non-digit characters.

Explanation of the Pattern

• %[^0-9]% matches any string that contains at least one character that is not a digit.
  
• NOT LIKE ensures such strings are excluded.
  
• This logic adds an extra layer of precision to the filtering process.
  

When to Use ISNUMERIC in SQL Workflows

Using ISNUMERIC in combination with CAST is a good practice in the following situations:

• When importing raw text data from external systems that may contain inconsistent formatting.
  
• In ETL pipelines where pre-validation of data is needed before transformation.
  
• During development and testing when data quality is not guaranteed.
  
• In reporting queries where only clean, valid numeric data should be considered.
  
• To help identify and isolate invalid records for further review.
  

This method allows you to keep your queries free from conversion errors and gives you more control over which values are processed.

Comparing ISNUMERIC + CAST with TRY_CAST

Both approaches are useful, but they serve slightly different purposes. ISNUMERIC combined with CAST gives you more control and can be fine-tuned with additional filtering. TRY_CAST, on the other hand, is simpler and automatically handles failures by returning NULL.

Here is a comparison:

Feature	ISNUMERIC + CAST	TRY_CAST
Error Handling	Avoids conversion on bad data	Returns NULL for bad data
Filtering Control	High (can add custom conditions)	Low (no filtering, just conversion)
SQL Version Requirement	SQL Server 2000+	SQL Server 2012+
Custom Pattern Validation	Supported via LIKE or PATINDEX	Not applicable
Readability	Slightly more complex	Very simple

Choose the method that best suits your use case. For production-grade scripts, using both together can offer the highest level of control and safety.

Conclusion 

Using ISNUMERIC with CAST is a powerful technique for converting NVARCHAR to INT in SQL when you need to control the validity of your input data. It allows you to pre-filter non-numeric values and avoid runtime errors while maintaining the integrity of your results.

Although it comes with some limitations, such as the inability to distinguish between different numeric formats, it remains a valuable tool in any SQL developer’s toolkit. When combined with pattern checks and validation logic, it becomes even more effective at cleaning and preparing data for analysis or reporting.

This completes the full exploration of different methods to convert NVARCHAR to INT in SQL. Each method—CAST, CONVERT, TRY_CAST, TRY_CONVERT, and ISNUMERIC + CAST—has its own use case and benefits. Selecting the right one depends on the data you are dealing with, the SQL Server version, and your specific goals.