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SQL for Data Analytics

You're reading from SQL for Data Analytics Perform fast and efficient data analysis with the power of SQL

Product type Paperback

Published in Aug 2019

Publisher Packt

ISBN-13 9781789807356

Length 386 pages

Edition 1st Edition

Languages

SQL

Tools

PostgreSQL

Concepts

Data Analysis

Authors (3):

Benjamin Johnston

Matt Goldwasser

Upom Malik

View More author details

Table of Contents (11) Chapters

Preface

About the Book

1. Understanding and Describing Data

2. The Basics of SQL for Analytics FREE CHAPTER

3. SQL for Data Preparation

4. Aggregate Functions for Data Analysis

5. Window Functions for Data Analysis

6. Importing and Exporting Data

7. Analytics Using Complex Data Types

8. Performant SQL

9. Using SQL to Uncover the Truth – a Case Study

Appendix

9. Using SQL to Uncover the Truth – a Case Study

Learning Objectives

By the end of this chapter, you will be able to:

Use the scientific method and critical thinking to glean insights about your data
Solve real-world problems outside of those described within this book by using the skills that you have acquired
Convert data and hypotheses into actionable tasks and insights
Use the skills developed in this book to solve problems in your specific problem domain

In this chapter, we will examine an extensive and detailed real-world case study of sales data. This case study will not only demonstrate the processes used in SQL analysis to find solutions for actual problems but will also provide you with confidence and experience in solving such problems.

The rest of the chapter is locked

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Authors (3)

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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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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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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