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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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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

T-SQL aggregate queries

Data exploration and descriptive or comparative statistics are very important tasks that have to be done repeatedly and iteratively during every data science project. This gives us better insight into the data that we want to process throughout all projects. T-SQL aggregate queries are an important part of data exploration.

A T-SQL aggregate query is a kind of query that basically summarizes groups of records from underlying datasets and typically provides aggregated numeric values for each group of records generated from the dataset. Groups of records are not needed for every case or every assignment. Such aggregation queries give an aggregation of summarized values over whole underlying datasets.

The simplest aggregation query does not require grouping. With or without grouping, aggregate queries use special kinds of functions, called aggregate functions...

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