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Renee M Teate

SQL for Data Scientists: A Beginner's Guide for Building Datasets for Analysis 1st Edition

by Renee M. P. Teate (Author)

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Jump-start your career as a data scientist―learn to develop datasets for exploration, analysis, and machine learning

SQL for Data Scientists: A Beginner's Guide for Building Datasets for Analysis is a resource that’s dedicated to the Structured Query Language (SQL) and dataset design skills that data scientists use most. Aspiring data scientists will learn how to how to construct datasets for exploration, analysis, and machine learning. You can also discover how to approach query design and develop SQL code to extract data insights while avoiding common pitfalls.

You may be one of many people who are entering the field of Data Science from a range of professions and educational backgrounds, such as business analytics, social science, physics, economics, and computer science. Like many of them, you may have conducted analyses using spreadsheets as data sources, but never retrieved and engineered datasets from a relational database using SQL, which is a programming language designed for managing databases and extracting data.

This guide for data scientists differs from other instructional guides on the subject. It doesn’t cover SQL broadly. Instead, you’ll learn the subset of SQL skills that data analysts and data scientists use frequently. You’ll also gain practical advice and direction on "how to think about constructing your dataset."

Gain an understanding of relational database structure, query design, and SQL syntax
Develop queries to construct datasets for use in applications like interactive reports and machine learning algorithms
Review strategies and approaches so you can design analytical datasets
Practice your techniques with the provided database and SQL code

In this book, author Renee Teate shares knowledge gained during a 15-year career working with data, in roles ranging from database developer to data analyst to data scientist. She guides you through SQL code and dataset design concepts from an industry practitioner’s perspective, moving your data scientist career forward!

ISBN-10

1119669367
ISBN-13

978-1119669364
Edition

1st
Publication date

August 27, 2021
Language

English
Dimensions

7.38 x 0.65 x 9.25 inches
Print length

288 pages
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Editorial Reviews

From the Inside Flap

Jumpstart your data science career with crucial SQL skills

Today, many organizations expect their data scientists to be able to design and generate their own datasets by extracting and combining raw data from the company’s data warehouses without the assistance of data engineers.

In SQL for Data Scientists: A Beginner’s Guide for Building Datasets for Analysis, experienced data scientist and database developer Renée M. P. Teate delivers a singular guide to the SQL skills and techniques every data scientist should know. You’ll discover how to approach query design and develop SQL code to construct datasets for exploration, analysis, and data science.

SQL for Data Scientists shows you how to create datasets for use in applications like interactive reports and dashboards, as well as in machine learning algorithms. You’ll skip right to the subset of SQL skills that data scientists and analysts use most frequently, and receive expert advice on extracting insights from data while avoiding common pitfalls.

Understand fundamental SQL syntax and design effective SQL queries
Conduct Exploratory Data Analysis with SQL
Construct, filter, and sort your own datasets from pre-existing databases
Use SQL JOINs to combine data from multiple database tables
Design datasets for analytical reports and machine learning applications
Apply more advanced SQL techniques such as Window Functions and Common Table Expressions
Create database tables and views to store and retrieve the results of your queries

From the Back Cover

Jumpstart your data science career with crucial SQL skills

Today, many organizations expect their data scientists to be able to design and generate their own datasets by extracting and combining raw data from the company’s data warehouses without the assistance of data engineers.

In SQL for Data Scientists: A Beginner’s Guide for Building Datasets for Analysis, experienced data scientist and database developer Renée M. P. Teate delivers a singular guide to the SQL skills and techniques every data scientist should know. You’ll discover how to approach query design and develop SQL code to construct datasets for exploration, analysis, and data science.

SQL for Data Scientists shows you how to create datasets for use in applications like interactive reports and dashboards, as well as in machine learning algorithms. You’ll skip right to the subset of SQL skills that data scientists and analysts use most frequently, and receive expert advice on extracting insights from data while avoiding common pitfalls.

Understand fundamental SQL syntax and design effective SQL queries
Conduct Exploratory Data Analysis with SQL
Construct, filter, and sort your own datasets from pre-existing databases
Use SQL JOINs to combine data from multiple database tables
Design datasets for analytical reports and machine learning applications
Apply more advanced SQL techniques such as Window Functions and Common Table Expressions
Create database tables and views to store and retrieve the results of your queries

Product details

Publisher ‏ : ‎ Wiley; 1st edition (August 27, 2021)
Language ‏ : ‎ English
Paperback ‏ : ‎ 288 pages
ISBN-10 ‏ : ‎ 1119669367
ISBN-13 ‏ : ‎ 978-1119669364
Item Weight ‏ : ‎ 1 pounds
Dimensions ‏ : ‎ 7.38 x 0.65 x 9.25 inches

Best Sellers Rank: #173,570 in Books (See Top 100 in Books)
- #33 in SQL
- #72 in Data Mining (Books)
- #104 in Data Processing

Customer Reviews:
62 ratings

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Renee M Teate

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Renée M. P. Teate is the Director of Data Science at HelioCampus, leading a team that builds predictive models for colleges and universities. She has worked with data professionally since 2004, in roles including relational database design, data-driven website development, data analysis and reporting, and data science. With degrees in Integrated Science and Technology from James Madison University and Systems Engineering from the University of Virginia, along with a varied career working with data at every stage in a number of systems, she considers herself to be a “data generalist”.

Renée regularly speaks at technology and higher ed conferences and meetups, and writes in industry publications about her data science work and about navigating data science career paths. She also created the “Becoming a Data Scientist” podcast and @BecomingDataSci twitter account, where she’s known to her over 60k followers as “Data Science Renee”. She always tells aspiring data scientists to learn SQL, since it has been one of the most valuable and enduring skills needed throughout her career.

Customer reviews

4.7 out of 5

62 global ratings

5 star		73%
4 star		21%
3 star		4%
2 star		2%
1 star 0% (0%)		0%

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Top reviews from the United States

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Raz Karcy

Concise & Thorough

Reviewed in the United States 🇺🇸 on January 31, 2023

Verified Purchase

As a beginner in SQL but not to programming, I am finding this book invaluable. The author's writing style is direct and clear. Chapters are not overly long. She is not a wordy writer, which I appreciate. 5 stars.

Helpful

Leo Angora

Content is invaluable

Reviewed in the United States 🇺🇸 on April 17, 2022

Verified Purchase

This book is a must-have for aspiring data scientists. Its content and online companion material is a treasure. I wish the build quality was better, though. Both paper and cover feel cheap, practically indistinguishable from a photocopy.

Helpful

Di

An excellent guide, from basics to building machine learning data sets

Reviewed in the United States 🇺🇸 on November 16, 2021

Verified Purchase

A practical how-to and reference guide for both the new and seasoned SQL-er. It's full of examples. Almost every page has a bit of code in it, illustrating the concepts one at a time. Comprehensive and accessible.

2 people found this helpful

Helpful

Amazon Customer

SQL for Data Scientists

Reviewed in the United States 🇺🇸 on December 29, 2021

Verified Purchase

Book is easy to read. Likely useful for someone with no knowledge. Giving examples of extension to a statistical package would have added value to the usefulness of the book.

One person found this helpful

Helpful

SueL

Best SQL Book ever

Reviewed in the United States 🇺🇸 on January 6, 2022

I used this book as part of a University module and it was perfect. The sample data, assignments and case studies were interesting and so easy to follow. It is also perfectly structured and great as a reference guide. Highly recommend this book to everyone!

One person found this helpful

Helpful

Top reviews from other countries

Mbos

Finally an SQL book I read all the way through

Reviewed in Australia 🇦🇺 on September 29, 2021

Verified Purchase

First of all even though the title is SQL for Data Scientist don't be thrown off if you are not a data scientist.

I come from a finance background where MS Excel was the only analytical tool available to me from a work standpoint, having transitioned away from Excel and into Power BI I have found that this is one of the few SQL books that I was able to read from start to end. The layout makes it easy to follow, the formatting also makes this an enjoyable resource, unlike many other SQL books out there.

The chapters are perfect what for I needed, now that I need to use AWS, Tableau and Alteryx this book has been an awesome resource. I have bought both formats of the book and I recommend this book those that need to learn SQL no matter what your background.

One person found this helpful

Ram

Book content is excellent, but printing looks like a pirated copy.

Reviewed in India 🇮🇳 on October 2, 2022

Verified Purchase

Five stars for content, but two for printing. Content is excellent, but I think I got a pirated copy. Printing is not sharp, but smudged/spread. It seems like cheap reprint of original.

One person found this helpful

Brian Jaeger

Well structured, accessible SQL primer

Reviewed in Germany 🇩🇪 on September 1, 2021

Verified Purchase

Bought the book on Kindle, very happy - it's well structured, accessible and thorough, exactly what I wanted.

One person found this helpful

See all reviews