Old faithful is renewed – welcome to Cubes as a Service

Analysis Services (as a) Service

For BI professionals, the main component used to provide a rich business-friendly enterprise information layer to non-technical users at scale was SQL Server Analysis Services (Power BI models achieves the same, but is limited by scale).

One major downside of Analysis Services was its requirement to be on premise (with “on premise” I of course include Virtual Machines through Infrastructure as a Service) – so no modern analytics architecture that included Analysis Services could claim to be server-less, and such modern cutting edge Analytics Architectures therefore always required a bit of the old (the other components in the same camp are Reporting- and Integration Services).

This will soon no longer be the case, Microsoft recently announced Analysis Services Service. This is basically Cubes as a Service.

 (Grinslade, 2016)

We feel once this service is released for General Availability, it will be a become a very common component in any large and modern Data Analytics landscape.

The benefits:

·       Arguably the most important benefit is cost – (following the pattern used by Microsoft for their Data warehouse as a Service, SQLDW) is the ability to pause the service, which means, together with scaling up or down, you pay only for what you use. There are major cost benefits associated with this compared to maintaining servers (incl. IaaS) to host Analysis Services.

·       It makes moving the business from on premise to the cloud much simpler.

·       It helps achieve a server-less eco system which means the cloud provider (in this case Microsoft) can take care of commoditised services (like infrastructure, availability and recovery).

·       It is easy to scale (through Query Processing Units) and to pause.

·       The service is in the cloud, so connecting to cloud data sources is as expected very simple, and connecting to on premise data sources is enabled through the on premise data gateway (you may already use this in your Power BI solutions, and if not it is very easy to deploy).

 caas-sources

 

 (Duncan, 2016)

·       One of the downsides of the (underlying) data model created in Power BI (in Import mode) is that fact that it is a black box, not accessible by other BI tools. Analysis Services Service overcomes this limitation.

caas-visualisations

 

 (Duncan, 2016)

Purely Technical benefits

·       The service is built on SQL Server 2016 Analysis Services Enterprise Edition so for those BI professionals familiar with this technology there is no new skills to learn.

·       There is a time benefit – technical professionals can now spend their time developing truly great Analysis Services solutions without having to be distracted by infrastructure challenges (like setting up and configuring servers to host the solution).

The service is still in its infancy and many things simply do not work, but we will be test driving it in due course, so watch out for a blog post once it goes into General Availability.

Let’s hope Microsoft embraces the same strategy for Integration Services (ETL) and Reporting Services (paginated reports)

References

Duncan, O. (2016, October 26). What is Azure Analysis Services? Retrieved from https://azure.microsoft.com/en-us/documentation/articles/analysis-services-overview/

Grinslade, B. (2016, October 25). Announcing Azure Analysis Services preview. Retrieved from https://azure.microsoft.com/en-us/blog/introducing-azure-analysis-services-preview/

Microsoft. (n.d.). Azure Analysis Services. Retrieved from https://azure.microsoft.com/en-us/services/analysis-services/

 

 

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