Scaling Analysis Services in Windows Azure
Windows Azure offers great potential for small to medium sized applications.
However, especially for Analysis Services such applications can easily become
also quite big very fast. For on-premises solutions this is very common and
various solutions have already been proven to work also for bigger scale
implementations. However, things get different when it comes to Windows Azure.
Single hardware resources are still limited and therefor different approaches
need to be used. In this session I will show how different scale-up and
scale-out scenarios can be implemented in Windows Azure, thereby mainly
focusing on performance and manageability.
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I have been working with Microsoft BI tools since mid 2006 thereby mainly focusing on Microsoft SQL Server and its components, primary Analysis Services. In 2012 I achieved the SSAS Maestro certification and also received the Microsoft Community Contributor (MCC) award the second time in a row. With the release of SQL Server 2012 and Power BI I started shifting my focus towards there, especially to Power Pivot and DAX thereby also investigating into SSAS Tabular Models in detail. At about the same time I did my first steps with Windows Azure while trying to combine it with the other technologies I am by now already very familiar with.
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