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Hands-On Data Science with SQL Server 2017

You're reading from   Hands-On Data Science with SQL Server 2017 Perform end-to-end data analysis to gain efficient data insight

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Product type Paperback
Published in Nov 2018
Publisher Packt
ISBN-13 9781788996341
Length 506 pages
Edition 1st Edition
Languages
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Authors (2):
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Vladimír Mužný Vladimír Mužný
Author Profile Icon Vladimír Mužný
Vladimír Mužný
Marek Chmel Marek Chmel
Author Profile Icon Marek Chmel
Marek Chmel
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Toc

Table of Contents (14) Chapters Close

Preface 1. Data Science Overview FREE CHAPTER 2. SQL Server 2017 as a Data Science Platform 3. Data Sources for Analytics 4. Data Transforming and Cleaning with T-SQL 5. Data Exploration and Statistics with T-SQL 6. Custom Aggregations on SQL Server 7. Data Visualization 8. Data Transformations with Other Tools 9. Predictive Model Training and Evaluation 10. Making Predictions 11. Getting It All Together - A Real-World Example 12. Next Steps with Data Science and SQL 13. Other Books You May Enjoy

Questions

  1. Which external languages are supported by SQL Server?
    Python and R.
  2. Which service must be running for the successful execution of external code?
    SQL Server Launchpad.
  3. Can we combine filestreams with temporal tables?
    No, temporal tables do not support the versioning of filestream data.
  4. We are calling the following code: exec sp_execute_external_script @language = 'R', @script = '';. The script does not work and returns an error. Why?
    Every parameter of the procedure is of the nvarchar data type. All parameter values must start with a leading capital N: N'text in the parameter'.
  5. We are calling the sp_execute_external_script stored procedure. Inside the R script, we have the following line: Outputdataset <- as.data.frame(1+1);. The code does not return a result. Why?
    This is because the R language is case-sensitive. The correct casing is...
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