SA0277 : The inserted or updated value is incompatible with the target column type, potentially causing implicit conversion or data truncation

Implicit conversion, truncation, or data loss may occur if the inserted or updated value is not compatible with the target column type.

Description

When inserting or updating data in SQL Server, it’s crucial to ensure that the data types of the values being inserted or updated match the data types defined for the target columns. If there is a mismatch, SQL Server may attempt to implicitly convert the values, which can lead to unexpected results, such as data loss or truncation. These issues can occur during both insertions and updates, causing integrity problems in the database.

For example:

SQL
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1-- Example of problematic update statement
2UPDATE TableName
3SET NumericColumn = '123.45' 
4WHERE Id = 1;

In this example, the value ‘123.45’ is a string and may not be correctly converted to a numeric type, depending on the context. If the column NumericColumn is defined as an integer, attempting to set it with a string value may result in a conversion error, or if it is a decimal, it could lead to truncation.

  • Implicit conversions can create performance overhead, as SQL Server must evaluate the type conversions at runtime, which can slow down execution.

  • Data loss can occur if values are truncated or rounded during conversion, leading to corrupted data and potential issues in data integrity.

How to fix

To resolve data type compatibility issues in SQL Server, ensure that all inserted or updated values match the data types of the target columns to prevent conversion errors and data truncation.

Follow these steps to address the issue:

  1. Review the data types of the target columns in your table using the sp_help stored procedure or SQL Server Management Studio (SSMS).

  2. Compare the data types of the values you are inserting or updating with the target columns to ensure compatibility.

  3. If there is a mismatch, either convert the value to the appropriate data type using CAST or CONVERT, or adjust the column data type accordingly.

For example:

SQL
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1-- Correcting type compatibility in an update statement
2UPDATE TableName
3SET NumericColumn = CAST('123.45' AS DECIMAL(10, 2)) 
4WHERE Id = 1;
5
6-- Ensuring the target column data type supports the inserted value
7INSERT INTO TableName (NumericColumn)
8VALUES (CAST('123.45' AS DECIMAL(10, 2)));

Scope

The rule has a Batch scope and is applied only on the SQL script.

Parameters
Name Description Default Value
IgnoreNumericDecimalScaleTruncations

Ignore data loss warning when source has higher scale than the scale of the target.

no
Remarks

The rule requires Analysis Context. If context is missing, the rule will be skipped during analysis.

Effort To Fix
20 minutes per issue.
Categories

Additional Information
Example Test SQL
SQL
Copy
 1DECLARE @table1 TABLE (
 2    VarCol VARCHAR(5) NULL,
 3    DecCol DECIMAL(5,2) NULL,
 4    DecCol2 DECIMAL(5,2) NULL
 5);
 6
 7DECLARE @table2 TABLE (
 8    VarCol VARCHAR(4) NULL,
 9    DecCol DECIMAL(5,1) NULL,
10    DecCol2 DECIMAL(4,2) NULL
11);
12
13-- Insert values that fit within the defined column types
14INSERT INTO @table1 (VarCol, DecCol, DecCol2)
15VALUES ('1234', 123.45, 12.34);
16
17UPDATE @table1 SET  VarCol = '1234', DecCol = 123.45,  DecCol2 = 12.34
18WHERE VarCol = '123';
19
20-- Implicit conversions with potential issues
21INSERT INTO @table2 (VarCol, DecCol, DecCol2)
22SELECT VarCol, DecCol, DecCol2 FROM @table1;
23
24UPDATE t2 SET VarCol = t1.VarCol, DecCol = t1.DecCol, DecCol2 = t1.DecCol2
25FROM @table2 t2 
26INNER JOIN @table1 t1 ON t2.VarCol = t1.VarCol;
27
28-- Attempting to insert potentially incompatible data
29INSERT INTO @table2 (VarCol)
30SELECT VarCol FROM @table1; -- String truncation error
31
32INSERT INTO @table2 (DecCol2)
33SELECT DecCol2 FROM @table1; -- Arithmetic overflow error
34
35-- Invalid data insert attempts
36INSERT INTO @table2 
37SELECT '12345678', '123.45', GETDATE() 
38UNION ALL 
39SELECT 'ABCDEF', 99999.99, 123.45;
40GO
Analysis Results
  Message Line Column
1 SA0277 : Possible truncation of value assigned to column VarCol – (varchar(5) to varchar(4)). 22 7
2 SA0277 : Possible truncation of value assigned to column DecCol – (decimal(5,2) to decimal(5,1)). 22 15
3 SA0277 : Possible truncation of value assigned to column DecCol2 – (decimal(5,2) to decimal(4,2)). 22 23
4 SA0277 : Possible truncation of value assigned to column – (varchar(5) to varchar(4)). 24 21
5 SA0277 : Possible truncation of value assigned to column – (decimal(5,2) to decimal(5,1)). 24 41
6 SA0277 : Possible truncation of value assigned to column – (decimal(5,2) to decimal(4,2)). 24 62
7 SA0277 : Possible truncation of value assigned to column VarCol – (varchar(5) to varchar(4)). 30 7
8 SA0277 : Possible truncation of value assigned to column DecCol2 – (decimal(5,2) to decimal(4,2)). 33 7
9 SA0277 : Possible truncation of value assigned to column VarCol – (varchar(8) to varchar(4)). 37 7
10 SA0277 : Possible truncation of value assigned to column VarCol – (varchar(6) to varchar(4)). 39 7
…
13 SA0277 : Explicit conversion will occur when assigning value to column DecCol2 – (datetime to decimal(4,2)). 37 29
14 SA0277 : Possible truncation of value assigned to column DecCol2 – (decimal(5,2) to decimal(4,2)). 39 27
See Also

Other Resources

Analysis Rules