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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

Summary

SQL Server is a relational database management system, but that does not mean we can rely only on data inside SQL Server for our analysis. There are several services and components in SQL Server that allow us to access data in structured, semi-structured, or even an unstructured form, and either query such data directly in its original storage (external to SQL Server) or import the data into SQL Server and transform the data into a relational form for further processing and wrangling with other existing datasets. Since the data coming into SQL Server may have different formats and can come from reliable and less reliable data sources, you need to carefully check the data during the cleaning phase so that you'll not import wrong, missing, or duplicate values to your database.

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