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SQL Server 2017 Machine Learning Services with R

You're reading from   SQL Server 2017 Machine Learning Services with R Data exploration, modeling, and advanced analytics

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Product type Paperback
Published in Feb 2018
Publisher Packt
ISBN-13 9781787283572
Length 338 pages
Edition 1st Edition
Languages
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Authors (2):
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Julie Koesmarno Julie Koesmarno
Author Profile Icon Julie Koesmarno
Julie Koesmarno
Toma≈æ Ka≈°trun Kaštrun Toma≈æ Ka≈°trun Kaštrun
Author Profile Icon Toma≈æ Ka≈°trun Kaštrun
Toma≈æ Ka≈°trun Kaštrun
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Table of Contents (12) Chapters Close

Preface 1. Introduction to R and SQL Server FREE CHAPTER 2. Overview of Microsoft Machine Learning Server and SQL Server 3. Managing Machine Learning Services for SQL Server 2017 and R 4. Data Exploration and Data Visualization 5. RevoScaleR Package 6. Predictive Modeling 7. Operationalizing R Code 8. Deploying, Managing, and Monitoring Database Solutions containing R Code 9. Machine Learning Services with R for DBAs 10. R and SQL Server 2016/2017 Features Extended 11. Other Books You May Enjoy

Microsoft's commitment to the open source R language

With a growing popularity and community, R has become and continues to be a big player in the field of advanced analytics and data visualization. R and machine learning servers (or services) are not just buzzword that will be forgotten in the next cycle of SQL Server, but it is infiltrating more and more into different layers of open source and corporate software. In the past five years, many big analytical players have introduced R integration, interpreters, and wrappers for the R language, because of the language's practicality, usability, and inter-disciplinarily and open source orientation. As Microsoft's making a bold and strategic move toward being open source friendly, the use cases for integrating R in SQL Server are growing, making this move even more natural and at the right point in time. This move had been very well appreciated in the SQL community and the business as well.

In comparison to other big analytical tools, Microsoft took integration very seriously. It addressed many of the issues and limitations of the language itself, and created complete integration of R with the SQL Server in order to give the best user experience. Many competitors (such as SAS, IBM, SAP, and Oracle) have done similar integration, but failed to take into account many aspects that contribute to a holistic user experience. Microsoft has announced that joining the R consortium will give them the ability to help the development of the R language and to support future development. In addition, Microsoft has created its own package repository called MRAN (from CRAN, where M stands for Microsoft) and is giving support and SLA agreement for R as well, even though the language and engine is based on Open R (a free, open-sourced version). All these steps tell us how dedicated Microsoft is in bringing an open source, statistical and programming language into the SQL Server environment.

We can only expect more R integration into other services. For example, Power BI supports native R visuals (https://powerbi.microsoft.com/en-us/blog/r-powered-custom-visuals) since October 2016, and R language since December 2015. Therefore, I am a strong believer that R will soon be part of the whole SQL Server ecosystem such as SSAS, SSIS, and SSRS natively as well. With Azure Analysis Services, R is again one step closer to analysis services.

You have been reading a chapter from
SQL Server 2017 Machine Learning Services with R
Published in: Feb 2018
Publisher: Packt
ISBN-13: 9781787283572
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