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The Applied SQL Data Analytics Workshop

You're reading from The Applied SQL Data Analytics Workshop Develop your practical skills and prepare to become a professional data analyst

Product type Paperback

Published in Feb 2020

Publisher Packt

ISBN-13 9781800203679

Length 484 pages

Edition 2nd Edition

Languages

SQL

Tools

Anaconda

Concepts

Data Analysis

Authors (3):

Upom Malik

Benjamin Johnston

Matt Goldwasser

View More author details

Table of Contents (9) Chapters

Preface

1. Introduction to SQL for Analytics

2. SQL for Data Preparation FREE CHAPTER

3. Aggregate and Window Functions

4. Importing and Exporting Data

5. Analytics Using Complex Data Types

6. Performant SQL

7. The Scientific Method and Applied Problem Solving

Appendix

6. Performant SQL

Overview

By the end of this chapter, we will be able to optimize database use to allow queries to be executed with fewer resources. First, we will look at how a database engine performs basic queries by developing our understanding of the sequential scan. Next, we will look at optimizing SELECT queries by creating indexes on our tables that improve performance. We will also examine the benefits of using joins in place of other functionality. We will explore advanced functionality by creating custom functions for special computations and examine how to apply custom constraints on our database by leveraging triggers. Finally, we will learn about tools and techniques for terminating inefficient queries that are consuming our database resources.

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Authors (3)

Matt Goldwasser

Matt Goldwasser

Matt Goldwasser is the Head of Applied Data Science at the T. Rowe Price NYC Technology Development Center. Prior to his current role, Matt was a data science manager at OnDeck, and prior to that, he was an analyst at Millennium Management. Matt holds a bachelor of science in mechanical and aerospace engineering from Cornell University.

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Upom Malik

Upom Malik

Upom Malik is a data science and analytics leader who has worked in the technology industry for over 8 years. He has a master's degree in chemical engineering from Cornell University and a bachelor's degree in biochemistry from Duke University. As a data scientist, Upom has overseen efforts across machine learning, experimentation, and analytics at various companies across the United States. He uses SQL and other tools to solve interesting challenges in finance, energy, and consumer technology. Outside of work, he likes to read, hike the trails of the Northeastern United States, and savor ramen bowls from around the world.

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Benjamin Johnston

Benjamin Johnston

Benjamin Johnston is a senior data scientist for one of the world's leading data-driven MedTech companies and is involved in the development of innovative digital solutions throughout the entire product development pathway, from problem definition to solution research and development, through to final deployment. He is currently completing his Ph.D. in machine learning, specializing in image processing and deep convolutional neural networks. He has more than 10 years of experience in medical device design and development, working in a variety of technical roles, and holds first-class honors bachelor's degrees in both engineering and medical science from the University of Sydney, Australia.

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