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Description

This error indicates that a data masking operation in SAP S/4HANA was attempted on a database column that uses a data type not supported by the masking functionality. It typically occurs during data anonymization or compliance efforts where specific columns are targeted for masking.

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Error Message

ERR_MASKING_INVALID_COLUMN_DATATYPE

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Known Causes

3 known causes

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Unsupported Column Data Type

The data masking configuration attempts to apply masking to a database column whose data type is not officially supported by SAP S/4HANA's data masking capabilities.

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Misconfigured Masking Rule

The defined data masking rule or profile specifies an operation on a column whose data type is incompatible with the chosen masking technique or the column itself.

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Recent Schema Modification

A change in the underlying database schema altered the data type of a column previously configured for masking, rendering it incompatible with existing masking rules.

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Solutions

3 solutions available

1. Identify and Correct Unsupported Column Data Type for Masking medium

Determine which column has an unsupported data type and change it to a compatible type before applying masking.

1

Identify the table and column causing the error. This usually requires analyzing the logs of the masking process. The error message might provide a hint to the specific table or context where masking failed.

2

Consult SAP's documentation for the specific version of SAP S/4HANA and the masking tool being used (e.g., SAP Data Custodian, or native database masking features if applicable) to understand which data types are supported for masking operations.

3

If a column has an unsupported data type (e.g., LOB types, complex structures, or specific binary types not designed for masking), you will need to either:

a) **Exclude the column from masking:** Modify the masking configuration to skip this particular column.
b) **Convert the data type:** If feasible and appropriate for the business context, convert the column's data type to a supported one. This might involve creating a new column, migrating data, and then dropping the old one. **Caution:** This is a significant change and requires thorough testing and business approval.

4

Example of checking column data types in SAP HANA (if HANA is the underlying database):

SELECT TABLE_NAME, COLUMN_NAME, DATA_TYPE FROM "SYS"."TABLE_COLUMNS" WHERE TABLE_NAME = '<your_table_name>' AND COLUMN_NAME = '<your_column_name>';

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After making the necessary adjustments (either excluding the column or changing its data type), re-run the masking process.

2. Review and Adjust Masking Rules for Specific Column Types medium

Ensure that the masking rules applied to a column are compatible with its data type, especially for character-based or numerical types that might have length or format constraints.

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Pinpoint the exact masking rule and the column it's applied to that is triggering the error. This often requires examining the masking job configuration or script.

2

Understand the limitations of the masking rule. For instance, applying a 'mask with fixed string' to a very large text field might fail if the fixed string is too short, or applying a numerical masking function to a date field will definitely fail.

3

If the column is a character type (VARCHAR, NVARCHAR, etc.), ensure the masking rule's output length is compatible. Some masking functions might generate output that exceeds the column's defined length. Consider using masking functions that preserve length or allow for variable output.

4

If the column is a numerical type, ensure the masking rule is appropriate. For example, attempting to mask a decimal with a function expecting an integer might cause issues. Ensure the masking function's output format aligns with the column's precision and scale.

5

Modify the masking rule. This could involve:

a) Changing the masking function used.
b) Adjusting parameters of the masking function (e.g., length of the masked output, format).
c) If the column contains mixed data that the masking rule cannot handle, consider pre-processing the data or using a more sophisticated masking approach.

6

Test the adjusted masking rule on a small subset of data or a development environment before applying it to the full dataset.

3. Verify SAP S/4HANA Masking Tool Compatibility and Configuration advanced

Ensure the masking solution being used is compatible with your SAP S/4HANA version and its configuration is correctly set up for the underlying database.

1

Identify the specific masking solution in use. SAP S/4HANA can leverage various data masking techniques, including SAP Data Custodian, third-party tools, or native database features. The error might originate from the interface between S/4HANA and the masking tool.

2

Check the SAP Support Portal for any SAP Notes or KBA articles related to Error Code 5736 and your specific SAP S/4HANA version. There might be known issues or required patches for the masking functionality.

3

If using SAP Data Custodian or a similar SAP-provided tool, review its configuration. Ensure that the connection details to the S/4HANA database are correct and that the tool has the necessary permissions to query table schemas and apply masking operations.

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Verify that the masking tool's underlying engine or connectors are compatible with the specific database technology used by your SAP S/4HANA system (e.g., SAP HANA, Oracle, SQL Server). Data type handling can vary between database platforms.

5

If the masking is being performed at the database level (e.g., via SQL scripts or stored procedures), ensure the SQL syntax and data type handling are correct for the specific database version. For SAP HANA, this would involve checking HANA-specific SQL data types and functions.

6

Consider performing a dry run or a simulation of the masking process to capture more detailed error information that can help in diagnosing the root cause.

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Related Errors

5 related errors

SAP S/4HANA Error 5736: Invalid Data Type for Masking