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Beginning SQL Server R Services Analytics for Data Scientists /
Learn how to develop powerful data analytics applications quickly for SQL Server database administrators and developers. Organizations will be able to sift data and derive the business intelligence needed to drive business decisions and profit. The addition of R to SQL Server 2016 places a powerful...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Berkeley, CA :
Apress : Imprint: Apress,
2016.
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| Edición: | 1st ed. 2016. |
| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
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| 245 | 1 | 0 | |a Beginning SQL Server R Services |h [electronic resource] : |b Analytics for Data Scientists / |c by Bradley Beard. |
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| 520 | |a Learn how to develop powerful data analytics applications quickly for SQL Server database administrators and developers. Organizations will be able to sift data and derive the business intelligence needed to drive business decisions and profit. The addition of R to SQL Server 2016 places a powerful analytical processor into an environment most developers are already comfortable with - Visual Studio. This book walks even the newest of users through the creation process of a powerful R-language tool set for use in analyzing and reporting on your data. As a SQL Server database administrator or developer, it is sometimes difficult to stay on the bleeding edge of technology. Microsoft's addition of R to SQL Server 2016 is sure to be a game-changer, and the language will certainly become an integral part of future releases. R is in fact widely used today in statistical and related applications, and its use is only growing. Beginning SQL Server R Services helps you jump on board this important trend by providing good examples with detailed explanations of the WHY and not just the HOW. Walks you through setup and installation of SQL Server R Services. Explains the basics of working with R Tools for Visual Studio. Provides a road map to successfully creating custom R code. | ||
| 650 | 0 | |a Database management. | |
| 650 | 0 | |a Mathematical statistics-Data processing. | |
| 650 | 0 | |a Data mining. | |
| 650 | 0 | |a Compilers (Computer programs). | |
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| 650 | 2 | 4 | |a Statistics and Computing. |
| 650 | 2 | 4 | |a Data Mining and Knowledge Discovery. |
| 650 | 2 | 4 | |a Compilers and Interpreters. |
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