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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

Analytical barriers

Many companies encounter barriers when trying to analyse their data. These barriers are usually knowledge scarcity (not all departments have the knowledge to analyse the data) and data dispersity (usually data arrives from different sources).

Enterprises divide responsibilities according to the roles or functions of the employees. Such division of work has a positive effect, especially when an enterprise is large. Usually, small to mid-sized enterprises adopt such roles as well, but they are normally granulated on a higher level due to a smaller number of employees.

With rapid market changes, the emergence of new technologies, and the need for faster adaptation, many experts have noticed many of the following barriers:

  • Data scarcity and data dispersity
  • Complex (and many times outdated) architecture
  • Lack of knowledge
  • Low productivity
  • Slow adaptation to market...
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