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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

Questions

  1. How do aggregate functions evaluate NULL?
    The NULL value is almost ignored in aggregate functions. NULL is not a minimal nor maximal value. The only exception to this rule is the COUNT(*) aggregate function, because it works with whole records.
  2. When executing an aggregate query, the following error occurred: Column '#src.SubcategoryName' is invalid in the select list because it is not contained in either an aggregate function or the GROUP BY clause. What does this mean?
    This error means that we forgot to add a non-constant column to the GROUP BY clause from the SELECT clause.
  3. What are GROUPING SETS used for?
    When writing aggregate queries, we sometimes need to have more combinations of grouping criteria. GROUPING SETS are used to define several combinations of grouping in aggregate queries.
  4. How is the frame defined when the ranking function is used?
    When...
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