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  • When to Scale-Up or Scale-Out with Azure Analysis Services
    Of all the new features and capabilities currently available with Azure Analysis Services, dynamic scaling up/down and in/out are my 2 favorite. Scaling Up refers to adding more (CPU and/or memory) resources Scaling Out refers to adding more servers Together these features allow you to adjust resources to match changes...
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  • Methods for Deploying to Azure Analysis Services
    This post covers the most common methods for deploying tabular models while explaining the trade offs for each option. Here are some questions to help you decide which one is most appropriate for your environment: Will you (the SSAS expert) be deploying the solution or do you need to hand...
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  • Analysis Services in the Cloud: IaaS vs PaaS
    When deciding to deploy an Analysis Services solution to the cloud, one of the very first decisions to make is whether to go with an Infrastructure-as-a-Service or Platform-as-a-Service architecture. The diagram below does a good job in explaining the differences between the two. Source: http://www.hostingadvice.com/how-to/iaas-vs-paas-vs-saas/ Note: from an Analysis Services...
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  • What is Super DAX?
    In a recent post, I mentioned something called Super DAX without giving it a very detailed explanation. If you’ve been working with SSAS for a few years and have a couple of Tabular projects under your belt, you may already be familiar with some of the performance improvements that roll...
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  • SSAS Multidimensional and Super DAX
    An interesting question came up during a recent engagement involving Power BI reporting against a Multidimensional data source. The client wanted to know if there was any benefit for them in upgrading from SSAS 2014 Multidimensional to SSAS 2016 Multidimensional. My initial response was “no, there would be little benefit...
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