R and Python drive SQL Server 2017 into machine learning

R and Python drive SQL Server 2017 into machine learning

Microsoft last week announced a wave of new features for its data platform, along with the SQL Server 2017 name and what Microsoft calls a “production quality” beta release. Other important changes include a new containerized deployment model for databases, which simplifies installation on Windows and Linux.

But it was SQL Server’s new Machine Learning tools that grabbed my attention.

Machine Learning remains one of Microsoft’s big themes for 2017, and it’s an important segment of SQL Server 2017. Mixing code and data has always been part of SQL Server, first with T-SQL, then with the Azure-focused U-SQL, which extended T-SQL with C# elements. SQL Server 2016 added support for embedded R code, and SQL Server 2017 continues that evolution by improving its support for R and adding Python. (By renaming SQL Server 2016’s R Services to Machine Learning Services in SQL Server 2017, Microsoft has made clear where it’s aiming its SQL tools.)

Including R and Python in SQL Server works well for both the existing SQL Server audience and for data scientists who are unlikely to have experience with T-SQL. The two languages have become important data science tools, with statistical analysis baked deep into their DNA. R remains clearly focused on statistical analysis, while Python adds statistical tools to a popular and flexible scripting language.

With R aimed at statistical analysis experts, Python is perhaps the easiest on-ramp to analytical programming for the rest of us, especially with a wide choice of relevant packages that add new data analysis features to a familiar language.

With Python inside SQL Server, you can bring existing data and code together. Data is accessible directly, so there’s no need to extract query data sets, moving from storage to application. It’s a useful approach, especially where there are issues of data sovereignty and compliance. Your code runs inside the SQL Server security boundaries, triggered by a single call from T-SQL stored procedures.

Share it:
Share it:

[Social9_Share class=”s9-widget-wrapper”]

Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.

You Might Be Interested In

Who Owns AI?: The Rise of Artificial Intelligence Patent Law

26 May, 2022

Not so many years ago, artificial intelligence was largely the stuff of science fiction. (“A.I. Artificial Intelligence” was actually the …

Read more

TDengine Brings Open Source Time-Series Database to Kubernetes

28 Aug, 2022

TDengine today made available an update to its namesake open source time-series database so that it can now run on …

Read more

Data is money: stand by for the Gold Rush

3 Dec, 2016

The gold rush is on again, and once again it is centerd on the American West. The original gold rush …

Read more

Do You Want to Share Your Story?

Bring your insights on Data, Visualization, Innovation or Business Agility to our community. Let them learn from your experience.

Get the 3 STEPS

To Drive Analytics Adoption
And manage change

3-steps-to-drive-analytics-adoption

Get Access to Event Discounts

Switch your 7wData account from Subscriber to Event Discount Member by clicking the button below and get access to event discounts. Learn & Grow together with us in a more profitable way!

Get Access to Event Discounts

Create a 7wData account and get access to event discounts. Learn & Grow together with us in a more profitable way!

Don't miss Out!

Stay in touch and receive in depth articles, guides, news & commentary of all things data.