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Copy file name to clipboardExpand all lines: docs/analysis-services/analysis-services-samples.md
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title: "Analysis Services samples | Microsoft Docs"
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ms.custom:
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- "SQL2016_New_Updated"
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ms.date: "03/29/2017"
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ms.date: "06/28/2017"
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ms.prod: "sql-server-2016"
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ms.reviewer: ""
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ms.suite: ""
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Use the information here to find sample databases and projects to help you learn about and test your Analysis Services solutions.
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## Samples on GitHub
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[Git repo for Analysis Services](https://github.com/Microsoft/Analysis-Services) includes code samples and community projects.
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## Sample solutions and databases
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While no longer officially supported or updated, Adventure Works remains one of the most inclusive and robust sample datasets for learning about and testing Analysis Services. Analysis Services sample projects and databases, as well as examples in documenation, blog posts, and presentations use the Adventure Works 2014 sample data.
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A new collection of sample data, Wide World Importers, was introduced for SQL Server 2016. You can use Wide World Importers sample data to learn about and test Analysis Services; however, no tutorials, examples, or documentation are provided. The Wide World Importers dataset and schema do not support many of the features in Analysis Services. To learn more, see [Wide World Importers](https://msdn.microsoft.com/library/mt734199).
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## Other samples
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[AMO code sample for creating tabular models programmatically](http://go.microsoft.com/fwlink/?linkID=221036).
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[Whitepaper and Code Sample for Automated Partition Management](https://blogs.msdn.microsoft.com/analysisservices/2017/01/17/whitepaper-and-code-sample-for-automated-partition-management/)
Copy file name to clipboardExpand all lines: docs/analysis-services/comparing-tabular-and-multidimensional-solutions-ssas.md
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## <aname="bkmk_models"></a> Model Features
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The following table summarizes feature availability at the model level. Review this list to ensure that the feature you want to use is available in the type of model you plan to build.
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|||||
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|-|-|-|-|
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||Multidimensional|Tabular|Power Pivot|
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|Actions|Yes|No|No|
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|Aggregations|Yes|No|No|
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|Calculated Column|No|Yes|Yes|
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|Calculated Measures|Yes|Yes|Yes|
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|Calculated Tables|No|Yes <sup>1</sup>|No|
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|Custom Assemblies|Yes|No|No|
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|Custom Rollups|Yes|No|No|
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|Default Member|Yes|No|No|
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|Display folders|Yes|Yes <sup>1</sup>|No|
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|Distinct Count|Yes|Yes (via DAX)|Yes (via DAX)|
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|Drillthrough|Yes|Yes (detail opens in separate worksheet)|Yes|
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|Hierarchies|Yes|Yes|Yes|
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|KPIs|Yes|Yes|Yes|
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|Linked objects|Yes|Yes (linked tables)|No|
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|Many-to-many relationships|Yes|No (but there is [bi-directional cross filters](../analysis-services/tabular-models/bi-directional-cross-filters-tabular-models-analysis-services.md) at 1200 and higher compatibility levels)|No|
|Drillthrough|Yes|Yes (depends on client application)|
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|Hierarchies|Yes|Yes|
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|KPIs|Yes|Yes|
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|Linked objects|Yes|Yes (linked tables)|
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|M expressions|No|Yes<sup>1</sup>|
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|Many-to-many relationships|Yes|No (but there is [bi-directional cross filters](../analysis-services/tabular-models/bi-directional-cross-filters-tabular-models-analysis-services.md) at 1200 and higher compatibility levels)|
<sup>1</sup> See [Compatibility Level for Tabular models in Analysis Services](../analysis-services/tabular-models/compatibility-level-for-tabular-models-in-analysis-services.md) for information about functional differences between compatibility levels.
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**Supported Data Sources**
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Tabular models can import data from relational data sources, data feeds, and some document formats. You can also use OLE DB for ODBC providers with tabular models. Tabular models at the 1400 compatibility level offer a signifcant increase in the variety of data sources from which you can import from. This is due to the introduction of the modern Get Data data query and import features in SSDT.
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Tabular models can import data from relational data sources, data feeds, and some document formats. You can also use OLE DB for ODBC providers with tabular models. Tabular models at the 1400 compatibility level offer a significant increase in the variety of data sources from which you can import from. This is due to the introduction of the modern Get Data data query and import features in SSDT utilizing the M formula query language.
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Multidimensional solutions can import data from relational data sources using OLE DB native and managed providers.
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