What is Azure Analysis Services?

With Analysis Services, you can mashup and combine data from multiple data sources, define metrics, and secure your data in a single, trusted semantic data model. The data model provides an easier and faster way for your users to browse massive amounts of data with client applications like Power BI, Excel, Reporting Services, third-party, and custom apps.

Built on SQL Server Analysis Services

Azure Analysis Services is compatible with many great features already in SQL Server Analysis Services Enterprise Edition. Azure Analysis Services supports tabular models at the 1200 and 1400Compatibility levels Partitions, row-level security, bi-directional relationships, and translations are all supported. In-memory and DirectQuery modes mean lightning fast queries over massive and complex datasets.

Tabular models offer rapid development and are highly customizable. For developers, tabular models include the Tabular Object Model (TOM) to describe model objects. TOM is exposed in JSON through the Tabular Model Scripting Language (TMSL) and the AMO data definition language through the Microsoft AnalysisServices. Tabular namespace.

As more and more data is generated from a variety of connected devices and sensors, transforming this data into actionable insights and predictions in near real-time is now an operational necessity.

Azure Stream Analytics seamlessly integrates with Azure IoT Hub and Azure IoT Suite to enable powerful real-time analytics on data from your IoT devices and applications.

Additionally, Azure Stream Analytics is available on Azure IoT Edge. Azure Stream Analytics on IoT Edge empowers developers to deploy near-real-time analytical intelligence closer to IoT devices so that they can unlock the full value of device-generated data.

Azure Analysis Services is a new preview service in Microsoft Azure where you can host semantic data models. Users in your organization can then connect to your data models using tools like Excel, Power BI and many others to create reports and perform ad-hoc data analysis.

To understand the value of Azure Analysis Services, imagine a scenario where you have data stored in a large database. You want to make that data available to your business users or customers so they can do their own analysis and build their own reports. To do this, one option would be to give those users access to that database. Of course, this option has several drawbacks. The design of that database, including the names of tables and columns may not be easy for a user to understand. They would need to know which tables to query, how those tables should be joined, and other business logic that needs to be applied to get the correct results. They would also need to know a query language like SQL to even get started. Most often this will lead to multiple users reporting the same metrics but with different results.

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