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Error messages when you try to process a database or a cube in SQL Server 2005 Analysis Services: "The attribute key cannot be found" and "The record was skipped because the attribute key was not found"
Article ID: 922673 - View products that this article applies to.
In Microsoft SQL Server 2005 Analysis Services, you try to process a database or a cube by using SQL Server Business Intelligence Development Studio or SQL Server Management Studio. However, the process operation fails, and you receive the following error messages:
Error message 1
Errors in the OLAP storage engine: The attribute key cannot be found: Table: TableName, Column: ColumnName1, Value: Value1. Table: TableName, Column: ColumnName2, Value: Value2.
Error message 2
Errors in the OLAP storage engine: The record was skipped because the attribute key was not found. Attribute: generated attribute X of Dimension: DimensionName from Database: DatabaseName, Cube: CubeName, Measure Group: MeasureGroupName, Partition: PartitionName, Record: RecordNumber.
This issue occurs because a fact table for a cube has one or more records that contain an attribute key, and this attribute key does not exist in the corresponding dimension table. This behavior may occur when you have not processed the corresponding dimension before you process the cube or when the underlying tables actually have mismatched data. If the "Value:" field in the message has no number after it, the fact table must contain null data.
To resolve this issue, you must verify that your data source points to the following locations:
Use an existing attribute keyUpdate the records to use an existing attribute key by running a statement resembles the following:
Match the key values in the fact tableInsert additional rows into the dimension table to match the key values in the fact table. If null values exist, use one of the following methods:
Ignore the errorIf you want to process the database or the cube without correcting the data, you can set the error configuration for the process operation to ignore the error. You should only do this as a temporary workaround when you fix the underlying data. Otherwise, you may receive unexpected results from your multidimensional expressions (MDX) queries. To ignore the errors, follow these steps: