Data science is the hot topic nowadays.  Customers are looking to get more value out of their data.  This world includes a large skillset that may not intersect with more traditional relational databases.

The world of data science has now intersected squarely with the Microsoft data platform.  The first example I can think of recently is Machine Learning Studio in Azure.  This is a web based area for building and testing machine learning models.

Recently, Microsoft acquired Revolution Analytics, who develop robust tools for the open-source R language.  R is one of the languages that work inside of Azure Machine Learning.  This language will be integrated into SQL Server 2016 when it releases.

In my role with Microsoft, I need to articulate the newer features that exist, or are coming, with the Microsoft Data Platform.  How do I bridge that gap, understand our offerings, and how can you gain hands-on experience with these new tools?

Within our Azure platform, we have a premade virtual machine released recently, called the Microsoft Data Science Virtual Machine.

Inside of this virtual machine you can find the following tools, ready to use:

• Revolution R Open
• Anaconda Python distribution
• Visual Studio Community Edition
• Power BI desktop
• SQL Server Express edition
• Azure SDK

I encourage you to spin this environment up in Azure, and play around.

Let me know what you think of this, and where you feel Data Science will land in your data world.

Thank you!