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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

Denormalizing data

Data denormalization is the process of adjusting data from a structure that is better for transactional processing to a structure that is better for reporting or data science purposes. This section provides a brief overview of data normalization and looks at why we denormalize, what we denormalize, and how to denormalize.

Relational normalization

In relational databases, data should be saved in so-called normalized structures. The normalization of data structures is a process that discovers the best structure that is resistant against any uncertainties in data, user change requests, and so on. The normalization itself is controlled by a set of rules known as normal forms.

Every normal form describes how...

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