While this is a common choice in many companies, I also see Analysis Services deployed on large virtual machines that run on a server infrastructure not optimized for Analysis Services. When choosing SQL Server Analysis Services, you must manage all the details about hardware sizing, setup, deployment, configuration, and service upgrades. Today your backend options for a Tabular model are SQL Server Analysis Services, Azure Analysis Services, and Power BI Premium. Many of this article’s considerations do not apply to large models that just have many columns and/or many unique values in smaller tables. The database size is just a consequence of the table size. By large I mean databases with one or more tables over 200 million rows. However, when dealing with a large dataset, you want to use the engine on a separate backend infrastructure. Indeed, the same engine runs Power BI, Power Pivot for Excel, SQL Server Analysis Services, and Azure Analysis Services. The Tabular semantic model was introduced to a large number of Power BI users, and they take advantage of the Analysis Services technology starting with the free Power BI Desktop. So I wanted to do a quick recap of the points I commonly discuss in these conversations, and have them readily available for the next conversation… As a bonus, I get to share them with a larger audience! I often get questions about use cases for Azure Analysis Services. UPDATE : also read Choosing Azure Analysis Services or Power BI Premium for large datasets – SQLBI containing updates about Power BI Premium Gen2.
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