By: Siddharth Mehta | Comments (1) | Related: > Analysis Services Dimensions
Problem
In any SQL Server Analysis Services (SSAS) solution that has global users, one of the common requirements is the localization of data based on users locale. Users prefer to have the visual cues for the understand the data in their local language. In this tip we would understand how to add localization support to dimension attributes.
Solution
SSAS provides a feature called Translations that can be used to add localization support for a dimension. Let's walk through an example with a sample Customer dimension.
1: Consider we have a cube dimension named Customer with a few attributes as shown below.
2: Click on Translations tab, right-click and select "New Translation" tab. This should bring up a language selection tab. Select the language of your choice and click OK.
3: After the translation is created, based on the language selected, add the translated caption against the attributes. You can use translators like translate.google.com and find the translation in the target language, and add the same to the translation as shown below.
4: Deploy the cube, and browse the same using SQL Server Management Studio (SSMS). On the top of the browser you should be able to see a Language option, from where the user can select the language of choice. Select the target language as shown below.
5: Once the language has been selected, the captions in the translated / localized language would be displayed as shown below. Only the attribute captions would be selected in the localize language. This would help users to identify attributes of a dimension in a localized language.
Next Steps
- There are also translations available at the cube level. Try creating translations at the cube level to add localization support.
- Learn more about SQL Server Analysis Services:
About the author
Siddharth Mehta is an Associate Manager with Accenture in the Avanade Division focusing on Business Intelligence.This author pledges the content of this article is based on professional experience and not AI generated.
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