Once you've created an Analysis Services server resource in Azure, there may be some administration and management tasks you need to perform right away or sometime down the road. For example, run processing to the refresh data, control who can access the models on your server, or monitor your server's health. Some management tasks can only be performed in Azure portal, others in SQL Server Management Studio (SSMS), and some tasks can be done in either.
Azure portal
Azure portal is where you can create and delete servers, monitor server resources, change size, and manage who has access to your servers. If you're having some problems, you can also submit a support request.
SQL Server Management Studio
Connecting to your server in Azure is just like connecting to a server instance in your own organization. From SSMS, you can perform many of the same tasks such as process data or create a processing script, manage roles, and use PowerShell.
To get all the latest features, and the smoothest experience when connecting to your Azure Analysis Services server, be sure you're using the latest version of SSMS.
When using SSMS, before connecting to your server the first time, make sure your username is included in the Analysis Services Admins group. To learn more, see Server administrators and database users later in this article.
Before you connect, you need to get the server name. In Azure portal > server > Overview > Server name, copy the server name.
In SSMS > Object Explorer, click Connect > Analysis Services.
In the Connect to Server dialog box, paste in the server name, then in Authentication, choose one of the following authentication types:
Authentication type, Active Directory - Universal with MFA support, is recommended.
Note
If you sign in with a Microsoft Account, Live ID, Yahoo, Gmail, etc., leave the password field blank. You are prompted for a password after clicking Connect.
Windows Authentication to use your Windows domain\username and password credentials.
Active Directory Password Authentication to use an organizational account. For example, when connecting from a non-domain joined computer.
ALM Toolkit - An open-source schema compare tool for Analysis Services tabular models and Power BI datasets, most often used for application lifecycle management (ALM) scenarios. Perform deployment across environments and retain incremental refresh historical data. Diff and merge metadata files, branches and repos. Reuse common definitions between datasets. Read-only is required for query operations. Read-write is required for metadata operations. To learn more, see alm-toolkit.com.
DAX Studio – An open-source tool for DAX authoring, diagnosis, performance tuning, and analysis. Features include object browsing, integrated tracing, query execution breakdowns with detailed statistics, DAX syntax highlighting and formatting. XMLA read-only is required for query operations. To learn more, see daxstudio.org.
Server administrators and database users
In Azure Analysis Services, there are two types of users, server administrators and database users. Both types of users must be in your Microsoft Entra ID and must be specified by organizational email address or UPN. To learn more, see Authentication and user permissions.
Troubleshooting connection problems
When connecting using SSMS, if you run into problems, you may need to clear the login cache. Nothing is cached to disc. To clear the cache, close and restart the connect process.
Next steps
If you haven't already deployed a tabular model to your new server, now is a good time. To learn more, see Deploy to Azure Analysis Services.
Azure Analysis Services delivers enterprise-grade BI semantic modeling capabilities with the scale, flexibility, and management benefits of the cloud. Azure Analysis Services helps you transform complex data into actionable insights.
To be clear, currently there aren't any plans to deprecate AAS. There is a priority to focus investment on Power BI Premium for enterprise data modeling, and so the additional value provided by Power BI Premium will increase over time.
If we have huge volume of data , you want aggregation and want to do everything on a single environment , we should go with azure synapse analytics. If you have smaller dataset and already a model created and target is to put together reports and run some anlaysis then we should go for AAS.
It is inevitable to monitor the applications and services to maximize the availability, performance, reliability and consumption. Traditionally, Microsoft has always excelled in providing enterprise-grade platform services to run highly scalable and reliable applications.
Azure Analysis Services is a fully managed platform as a service (PaaS) that provides enterprise-grade data models in the cloud. Use advanced mashup and modeling features to combine data from multiple data sources, define metrics, and secure your data in a single, trusted tabular semantic data model.
Reduce time-to-insights on large and complex datasets. Fast response times mean your BI solution can meet the needs of your business users and keep pace with your business. Connect to real-time operational data using DirectQuery and closely watch the pulse of your business.
What do you like best about Azure Analysis Services? easy to use and implement ,easy to integrate with other microsft product ,best in class product support by microsoft team ,multiple number of feature availble to use ,used number of times by various user means great user frequancy.
Azure Databricks is an analytics service designed for big data and machine learning, and Azure Analysis Services is a fully managed platform-as-a-service (PaaS) that provides enterprise-grade data models in the cloud.
In a statement on the Azure console, Microsoft confirmed the Azure IoT Central service is being retired on March 31, 2027. “Starting on April 1, 2024, you won't be able to create new application resources; however, all existing IoT Central applications will continue to function and be managed.
In Azure Synapse, you can connect to various data sources including Azure SQL Database and Synapse Analytics itself, but Azure Analysis Services is not listed among the supported data sources for direct querying or data import within Synapse Analytics.
Microsoft Azure Analysis Services (AAS) is a fully-managed platform-as-a-service (PaaS) offering that delivers enterprise-grade data models in the cloud. When combined with CData Connect Cloud, AAS facilitates immediate cloud-to-cloud access to Databricks data for applications.
Databricks supports real-time data processing through its structured streaming feature, while Synapse offers stream analytics capabilities, enabling both platforms to handle real-time data workflows.
You can monitor Synapse Analytics workspaces and pools directly from their Azure portal pages. On the left sidebar menu, you can access the Azure Activity log, or select Alerts, Metrics, Diagnostic settings, Logs, or Advisor recommendations from the Monitoring section.
Azure Monitor is a comprehensive monitoring solution for collecting, analyzing, and responding to monitoring data from your cloud and on-premises environments. You can use Azure Monitor to maximize the availability and performance of your applications and services.
To access Azure Log Analytics, you need to sign in to the Azure portal with your Azure account. Once you're signed in, you can access Log Analytics by selecting it from the list of services in the portal. To use Log Analytics, you need to create a Log Analytics workspace in your Azure subscription.
Log Analytics is a tool in the Azure portal that's used to edit and run log queries against data in the Azure Monitor Logs store. You might write a simple query that returns a set of records and then use features of Log Analytics to sort, filter, and analyze them.
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