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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

Data Transformations with Other Tools

In Chapter 5, Data Transformation and Cleaning with T-SQL, we explored the need for data transformation for the purpose of data consolidation, accuracy checking, and cleansing. From there, we went on to learn how to explore data from a statistical point of view in Chapter 6, Data Exploration and Statistics with T-SQL. In Chapter 7, Data Visualization, we used some very helpful techniques for data visualization. Using techniques from all three of these chapters leads to the need to transform data once again.

This chapter is intended to explain how to replace missing values, normalize data, or standardize data used as an input into further machine learning models. For many of these tasks, T-SQL is an inadequate language, so we will use other tools and languages to meet our requirements.

In this chapter, we will learn the following topics:

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