Error

Error Code: 469

SAP S/4HANA Error 469: Unsupported Source Data Type

📦 SAP S/4HANA

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Description

This error indicates that a data type used in a source system or data object is not recognized or compatible with SAP S/4HANA's processing capabilities. It commonly occurs during data integration, migration, or when custom SQL/CDS views encounter invalid data type definitions.

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Error Message

ERR_SQL_INV_SRC_DATATYPE

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Known Causes

3 known causes

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Data Type Mismatch in Integration

During data integration or migration, a source system's data type does not have a valid or supported mapping to an SAP S/4HANA data type.

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Incorrect SQL/CDS Definition

A custom SQL query, CDS view, or ABAP code attempts to process data from a source field using an incompatible or undefined data type.

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External Data Source Incompatibility

An external data source provides data in a format or uses a data type that SAP S/4HANA cannot natively interpret or convert.

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Solutions

3 solutions available

1. Identify and Correct Incompatible Data Types in Data Migration/Integration medium

Ensures data types in the source system align with S/4HANA requirements during migration or integration.

Analyze the data migration or integration process that triggered the error. Pinpoint the specific table and column(s) involved in the `ERR_SQL_INV_SRC_DATATYPE` error. This often requires reviewing the logs of your ETL tool (e.g., SAP Data Services, Informatica, custom ABAP programs) or the SQL statements used.

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Compare the data types of the source table/fields with the corresponding target table/fields in S/4HANA. SAP S/4HANA uses specific SQL data types. Common incompatibilities arise with date/time formats, character string lengths, and numeric precision.

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For character data, ensure the source data type length is not exceeding the target S/4HANA field length. Truncate or adjust the source data if necessary.

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For numeric data, verify precision and scale. If the source has higher precision than the target, consider data rounding or adjusting the target field definition (if permissible and after thorough impact analysis).

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For date and time fields, ensure consistent formatting. S/4HANA typically expects formats like 'YYYYMMDD' for dates and 'HH24MISS' for times. Use conversion functions in your ETL tool or SQL to standardize these before loading.

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If using ABAP programs for data loading, review the data type declarations and conversions within the program. Ensure explicit type casting or appropriate handling of potential type mismatches.

ABAP
DATA: lv_source_char TYPE c LENGTH 100.
DATA: lv_target_char TYPE c LENGTH 50.

* Example: If source is longer than target
IF strlen( lv_source_char ) > 50.
  lv_target_char = lv_source_char(50).
ELSE.
  lv_target_char = lv_source_char.
ENDIF.

* Example: Date conversion
DATA: lv_source_date TYPE d.
DATA: lv_target_date TYPE d.

* Assuming lv_source_date is populated from a string with a different format
* Use appropriate conversion functions like 'CONVERT_DATE_TO_INTERNAL' or 'SYST_DATE_AS_CHAR' etc.

2. Adjust Source System Data Type Definitions advanced

Modifies data type definitions in the source system to be compatible with S/4HANA.

This solution is applicable when you have control over the source system's database schema and the data is not yet migrated or is being replicated. Identify the specific table and column causing the issue.

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Consult SAP S/4HANA documentation for the correct data types for the target table. For example, if you are loading into a standard SAP table, find the ABAP data dictionary definition.

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Modify the data type of the offending column in the source system database to match the S/4HANA requirement. For instance, change a `VARCHAR(255)` to a `VARCHAR(100)` if the S/4HANA field is `C(100)`.

SQL
-- Example for Oracle
ALTER TABLE your_source_table MODIFY ( your_column VARCHAR2(100) );

-- Example for SQL Server
ALTER TABLE your_source_table ALTER COLUMN your_column VARCHAR(100);

After altering the source, re-run the data migration or integration process. Ensure that any existing data in the modified column still conforms to the new, more restrictive type. Data cleansing might be required before the alteration.

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3. Leverage SAP S/4HANA Data Type Mapping Tools medium

Utilizes SAP-provided tools to manage and map data types during migration.

For SAP-to-SAP migrations (e.g., ECC to S/4HANA), SAP provides migration tools like SAP S/4HANA Migration Cockpit. These tools often have built-in data type mapping capabilities.

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When using the Migration Cockpit, access the relevant migration object. Within the object, there are often options to define or review data type mappings between the source and target fields.

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Identify the field causing the `ERR_SQL_INV_SRC_DATATYPE` error and adjust its mapping. This might involve specifying a conversion routine or a specific target data type.

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If using SAP Data Services, review the data flow design. The platform allows for explicit data type transformations and conversions at various stages of the data pipeline. Ensure that any field causing the error has a transformation rule that correctly maps its source type to a compatible S/4HANA type.

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