70-466 · Question #24
70-466 Question #24: Real Exam Question with Answer & Explanation
The correct answer is B: Remove the duplicate data from the DimGeography table.. The error message explicitly states that a duplicate attribute key was found for StateProvinceKey value '23' in the DimGeography table. SSAS requires that key columns for attribute hierarchies be unique within their dimension table (or within the scope of their parent in an attri
Question
- City
- State-Province
- Country The attributes have the following relationships defined: City > State-Province > Country. Each attribute has a key and a name sourced from the DimGeography table. During processing, you receive the following error message: "Errors in the OLAP storage engine: A duplicate attribute key has been found when processing: Table: 'dbo_DimGeography', Column: 'StateProvinceKey', Value: '23'. The attribute: 'State-Province'." You verify that the data is accurate. You need to ensure that the dimension Processes successfully. What should you do? CREATE TABLE [dbo].[DimGeography]( [DimensionKey] [int] IDENTITY(1,1) NOT NULL, [CityName] nvarchar NULL, [StateProvinceName] nvarchar NULL, [StateProvinceKey] [int] NOT NULL, [CountryKey] [int] NOT NULL, [CountryName] nvarchar NULL ) ON [PRIMARY]
Options
- ARelate the State-Province and Country attributes directly to the City attribute.
- BRemove the duplicate data from the DimGeography table.
- CRemove the State-Province attribute.
- DRemove the Country attribute.
Explanation
The error message explicitly states that a duplicate attribute key was found for StateProvinceKey value '23' in the DimGeography table. SSAS requires that key columns for attribute hierarchies be unique within their dimension table (or within the scope of their parent in an attribute relationship). Because the attribute relationship chain is City > State-Province > Country, SSAS expects each StateProvinceKey to map to exactly one unique member. The presence of duplicate rows with StateProvinceKey = 23 violates this constraint. The correct fix is to remove the duplicate rows from the source data (Option B). Option A would restructure relationships but would not fix the underlying data duplication. Options C and D would remove valid dimensional attributes and reduce analytical capability, rather than addressing the root cause.
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