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Microsoft: a power-house in Data and Analytics


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It’s been a remarkable year, even for an industry giant like Microsoft, as it has forged a dominant enterprise-class reputation for not only its public-cloud offerings via Azure, but also its specific data and analytics offerings. Even the most optimistic IoT strategist would probably concede that adopters are in danger of drowning in their own romantically named data lakes without utilising the right combination of data repositories and associated analytics tools to support the rapidly changing worlds of business and machine intelligence.

To meet this challenge, Microsoft has its SQL Server DBMS for the Operational DBMS market, as well as the Microsoft Azure SQL Database (a DBMS platform as a service), Azure Data Warehouse and the NoSQL DBMSs Microsoft Azure DocumentDB and Azure Tables. SQL Server 2016 brings Stretch Databases — on-premises databases "stretching" with partitions in the cloud to allow low-usage data to be demarcated in the now accepted paradigm of Hybrid IT. Microsoft has supported analytics access to the database with SSIS (Integration Services), SSAS (Analysis Services) and SSRS (Reporting Services). Microsoft will be offering the Azure Stack on-premise in the future, therefore opening up the same data and analytics tools without any potential sensitivity of holding data in the public cloud. Clearly Redcentric has impeccable industry credentials for holding such sensitive data in their own UK Data Centres. Microsoft has therefore long put behind it any lingering market perception of it as a provider of DBMSs for small, departmental applications. Gartner now sees Microsoft in 2016 as the clear leader in the DBMS market-place, based on a number of long-standing criteria.

For many years, Redcentric has tied its colours to the mast of Microsoft in terms of its SQL Server Managed Services practice and witnessed the rapid development of these enterprise offerings. However, Redcentric’s acceptance into the Azure Certified Solutions Partner programme by Microsoft has encouraged an even greater review of its Data and Analytics Offerings. The Cloud-based integration via Azure of a data gathering and visualisation toolset such as Power BI with Azure SQL Database provides a relatively simple conceptual starting-point to BI in the Cloud. This is supported by the easy-to-use migration toolsets for moving SQL and heterogeneous data from on-premise and the numerous features of the database platform as a service.

However, at the end of October 2016, it was announced that Analysis Services is now coming to Microsoft's cloud solution platform. Branded as Azure Analysis Services, it is based on the proven analytical engine embedded within SQL Server 2016 Analysis Services. Customers can access disparate data sources across on-premises and the cloud, model the data, and provide business users with a simplified view of their data to enable interactive self-service BI and data discovery using their preferred data visualization tool.

Azure Analysis Services delivers enterprise class BI semantic data modeling capabilities allowing you to access hybrid and cloud data from anywhere. Just like the other Azure offerings from Microsoft you can pause or shut down services and thereby pay only for the resources you need to consume. You're still able to use Visual Studio and other familiar tools to develop solutions utilizing Azure Analysis Services without needing to learn new tools. Plus you don’t need to spin up and support the infrastructure supporting Analysis Services in Azure because the platform is managed for you.

So, Microsoft Azure is an established cloud environment that is well designed to meet the needs of Microsoft users while delivering affordability and the kind of elastic scalability required of emerging database workloads. Power BI and Azure Analysis Services are just two of the Cloud flavours of BI capability that can be used to tap into the various forms of data that can be held either on-premise or in a public cloud.



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