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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 Sources for Analytics

In this chapter, we will review various sources of data that we can import and process in SQL Server for any analytical and data science techniques. This data can come from other database systems, flat files, application-specific files such as Excel, and web sources, among others. In regards to data structure, we can consider the data to be imported as structured, semi-structured, or unstructured. Based on the source and type of data, we have different tools in place that we can use to store the data in an SQL Server database.

We will cover the following topics in this chapter:

  • Getting data from databases
  • Importing flat files
  • Working with XML data
  • Working with JSON
  • External data with PolyBase
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