#Migrate ssas tabular to azure how to#
#Migrate ssas tabular to azure download#

So what are the options to carry on developing the model? We could still use VS and deploy the model to the XMLA endpoint. It’s common to use Visual Studio with Analysis Services extension to author models deployed to AAS.

#Migrate ssas tabular to azure download#

We can perform the migration repeatedly so if any changes are made to the AAS model then it can be migrated again into Power BI.Īfter the migration has been performed, there is no ability to download the model to author in Power BI Desktop.

Click the Azure Analysis Services migrations option.

The XMLA endpoint must be Enabled for read-write for the capacity.

Large dataset storage format must be enabled for the workspace.

You must have an Azure Data Lake Storage Gen 2 (ADLS Gen 2) storage account in the same tenant and the workspace you’re migrating to must be connected to that storage account.

You must have Workspace administrator permission.

You need Power BI Premium per Capacity, Power BI Premium per User, or Power BI Embedded.

If Firewall is enabled for your server, ensure Allow access from the Power BI Service is set to On, or disable Firewall during migration.

Backup must be configured in AAS (we have a step for this in this blog).

You must have Server administrator permissions and belong to the Owner and/or Contributor roles for the Azure subscription.

Azure Analysis Services server and the Power BI workspace must be in the same tenant.

The Microsoft documentation has a list of pre-requisites here, in summary: So how does migrating via the Power BI service work? Let’s walkthrough an example below, which includes backing up the Azure Analysis Services server and configuring Azure Data Lake Gen2 connection in Power BI.

#Migrate ssas tabular to azure how to#

How to Migrate from Azure Analysis Services to Power BI Premium What’s also interesting is that as of January 2023, Microsoft has announced scale-out capability for Power BI Datasets in Premium capacities, a similar feature exists in Azure Analysis Services for scaling out read-replicas to improve concurrent performance. I like to visualise, so I created a simple image to show what it may look like to migrate several models from an Azure Analysis Services server to a Power BI Premium P1 tenant. Although we need to take care about vCore usage…it’s no good putting a lot of large models that fit within the Max Memory per dataset limit and then expecting high performance. So we don’t need to worry about the total amount of memory used on the AAS server but rather think of it as separate models? It appears so. The maximum dataset size permitted on a capacity may be smaller than the numbers in this column.” However, an amount of memory must be reserved for operations such as refreshes and queries on the dataset. “The Max memory per dataset (GB) column represents an upper bound for the dataset size. The official Microsoft documentation states: Shout out to Johnny Winter who pointed out the Max memory per dataset resource limit concept. I’m coming around to the idea of migrating into Power BI Premium after learning more about the internal architecture of Premium Gen2 and how it handles dataset sizes in memory….more on that in the next part. If we migrate to Power BI Premium are we not then just putting more pressure on the Power BI tenant we’re migrating to? And also depending on the size of the migration, it might require increasing the premium tier…more £££/$$$! But that’s probably going to be offset by the cost of the Azure Analysis Services server being migrated away from. After all, Azure Analysis Services is a standalone product and can be scaled up and out.

Good question…and one that I keep asking myself. And that’s because how Power BI Premium Gen2 allocates memory to Power BI Datasets. Now my thoughts around migrating from Azure Analysis Services have tended to be “well, if I have a 100GB Azure Analysis Services server with several models on…am I expected to buy a P4 with 100GB RAM?” Well, no. those pesky DAX calculations that explode the RAM usage… So whilst the actual technical process of migrating is fairly straight-forward (which we’ll go through later in this blog), understanding the size of the model at rest and also when being refreshed and when in use is the trickier part.

Technically, migrating is simple but understanding the size of the model at rest and also when being refreshed and when in use is the trickier part Links to all the Microsoft documentation is available in the References section.Īccelerate your migration experience from Azure Analysis Services to Power BI Premium with the automated migration tool | Microsoft Power BI Blog | Microsoft Power BI Here is the link to the official blog post announcement.

Configuring Azure Analysis Services Backups.

How to Migrate from Azure Analysis Services to Power BI Premium.