In April we announced the general availability of Azure Analysis Services, which evolved from the proven analytics engine in Microsoft SQL Server Analysis Services. The success of any modern data-driven organization requires that information is available at the fingertips of every business user, not just IT professionals and data scientists, to guide their day-to-day decisions. Self-service BI tools have made huge strides in making data accessible to business users. However, most business users don’t have the expertise or desire to do the heavy lifting that is typically required, including finding the right sources of data, importing the raw data, transforming it into the right shape, and adding business logic and metrics, before they can explore the data to derive insights.
With Azure Analysis Services, a BI professional can create a semantic model over the raw data and share it with business users so that all they need to do is connect to the model from any BI tool and immediately explore the data and gain insights. Azure Analysis Services uses a highly optimized in-memory engine to provide responses to user queries at the speed of thought.
In the video below, I demonstrate to Scott Hanselman how to use Azure Analysis Services over SQL Data Warehouse. In this scenario, Azure Analysis Services servers two major functions:
- It provides a semantic model which acts as a lens that your business users look through to get to their data. It presents your underlying database in a way which makes it easy for your users to query without needing to change the structure of that database.
- A very fast in memory data caching layer which can answer queries in a fraction of a second. The cache provides users interactive querying over billions of rows of data while reducing the load on the underlying data store.
See the whole video:
You can try the Azure Analysis web designer today to build your own models by linking to it from a server in the Azure portal.