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Data Wrangling with SQL

You're reading from Data Wrangling with SQL

Product type Book

Published in Jul 2023

Publisher Packt

ISBN-13 9781837630028

Pages 350 pages

Edition 1st Edition

Languages

Concepts

Data Engineering

Authors (2):

Raghav Kandarpa

Shivangi Saxena

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Table of Contents (21) Chapters

Preface

1. Part 1:Data Wrangling Introduction

2. Chapter 1: Database Introduction

3. Chapter 2: Data Profiling and Preparation before Data Wrangling

4. Part 2:Data Wrangling Techniques Using SQL

5. Chapter 3: Data Wrangling on String Data Types

6. Chapter 4: Data Wrangling on the DATE Data Type

7. Chapter 5: Handling NULL Values

8. Chapter 6: Pivoting Data Using SQL

9. Part 3:SQL Subqueries, Aggregate And Window Functions

10. Chapter 7: Subqueries and CTEs

11. Chapter 8: Aggregate Functions

12. Chapter 9: SQL Window Functions

13. Part 4:Optimizing Query Performance

14. Chapter 10: Optimizing Query Performance

15. Part 5:Data Science And Wrangling

16. Chapter 11: Descriptive Statistics with SQL

17. Chapter 12: Time Series with SQL

18. Chapter 13: Outlier Detection

19. Index

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20. Other Books You May Enjoy

Query execution plan

Understanding query execution plans is an essential aspect of query optimization. It refers to the steps that the database takes to retrieve the data from the database and return the results to the user. Understanding these steps is critical in identifying bottlenecks and inefficiencies in the query, which can then be addressed to improve the performance of the query:

What is a query execution plan? A query execution plan is a detailed map of the steps that the database takes to execute a SQL query. It shows the order in which the database accesses the data, the methods used to retrieve the data, and the resources required to run the query.
How can we view a query execution plan? Query execution plans can be viewed using tools provided by the database management system, such as the EXPLAIN PLAN in Oracle or the SHOWPLAN in SQL Server. These tools provide a graphical representation of the query execution plan, making it easier to understand and analyze...

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Authors (2)

Raghav Kandarpa

Raghav Kandarpa is an experienced Data Scientist in Finance and logistics industry with expertise in SQL, Python, Building Machine Learning Models, Financial Data Modelling, and Statistical Analysis. He holds a Masters' degree in Business Analytics specializing in Data Science from the University of Texas at Dallas.

See other products by Raghav Kandarpa

Shivangi Saxena

Shivangi Saxena is an experienced BI Engineer with proficiency in SQL, Data Visualization, and Statistical Analysis. She holds a master's degree in Information Technology and Management from the University of Texas at Dallas. She has several years of experience building several BI tools and products using SQL and BI reporting tools which has helped stakeholders to get visibility to the right data points

See other products by Shivangi Saxena

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