On October 25, 2016, Microsoft announced the public preview of Azure Analysis Services which enables an entirely Azure-based BI solution and provides the ability to analyze your company’s data to every user, not just IT and data scientists.
The Case for a Semantic Layer in Your BI Solution
To understand the benefits of leveraging Azure Analysis Services, you must first understand Analysis Services and semantic layers in general. Data access and use is needed everywhere, and as the amount of data within organizations grows, IT and/or Data Analyst resources are continually strained to deliver critical data to the end-users so they can leverage it to make decisions.
- are developed, secured, deployed and managed by IT teams.
- allow end users to consume and query the data easily, without the need for technical expertise.
- store calculations and KPIs in-memory, along with the tabular data, providing an extremely quick experience for the end-user retrieving insights from the data.
- are developed in a familiar environment: SQL Server Data Tools in Visual Studio.
1 Grinslade, Bret. Digital image. Announcing Azure Analysis Services Preview. Microsoft, 25 Oct. 2016. Web.
The Case for Consuming Analysis Services as a PaaS
Once the need for a BI semantic layer is agreed upon, the decision for leveraging Azure Analysis Services becomes a simple one. Delivering a complete BI solution, from data warehouse, semantic layer and visualization, without managing a single virtual machine is now possible.
- You only need to pay for the level of services you need, which can be scaled and paused based off your specific needs.
- You no longer need to focus on maintaining virtual machines to host your solutions, allowing you to devote your precious resources to making your data accurate and available.
Microsoft has added an important piece to the Azure puzzle with Azure Analysis Services. Microsoft continues to add important components that help IT professionals meet the demands of the ever-changing BI landscape.
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