• Complain

Renee M Teate - SQL for Data Scientists: A Beginners Guide for Building Datasets for Analysis

Here you can read online Renee M Teate - SQL for Data Scientists: A Beginners Guide for Building Datasets for Analysis full text of the book (entire story) in english for free. Download pdf and epub, get meaning, cover and reviews about this ebook. year: 2021, publisher: Wiley, genre: Home and family. Description of the work, (preface) as well as reviews are available. Best literature library LitArk.com created for fans of good reading and offers a wide selection of genres:

Romance novel Science fiction Adventure Detective Science History Home and family Prose Art Politics Computer Non-fiction Religion Business Children Humor

Choose a favorite category and find really read worthwhile books. Enjoy immersion in the world of imagination, feel the emotions of the characters or learn something new for yourself, make an fascinating discovery.

No cover
  • Book:
    SQL for Data Scientists: A Beginners Guide for Building Datasets for Analysis
  • Author:
  • Publisher:
    Wiley
  • Genre:
  • Year:
    2021
  • Rating:
    3 / 5
  • Favourites:
    Add to favourites
  • Your mark:
    • 60
    • 1
    • 2
    • 3
    • 4
    • 5

SQL for Data Scientists: A Beginners Guide for Building Datasets for Analysis: summary, description and annotation

We offer to read an annotation, description, summary or preface (depends on what the author of the book "SQL for Data Scientists: A Beginners Guide for Building Datasets for Analysis" wrote himself). If you haven't found the necessary information about the book — write in the comments, we will try to find it.

Jump-start your career as a data scientist--learn to develop datasets for exploration, analysis, and machine learningSQL for Data Scientists:A Beginners Guide for Building Datasets for Analysis is a resource thats 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 doesnt cover SQL broadly. Instead, youll learn the subset of SQL skills that data analysts and data scientists use frequently. Youll 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 practitioners perspective, moving your data scientist career forward!

Renee M Teate: author's other books


Who wrote SQL for Data Scientists: A Beginners Guide for Building Datasets for Analysis? Find out the surname, the name of the author of the book and a list of all author's works by series.

SQL for Data Scientists: A Beginners Guide for Building Datasets for Analysis — read online for free the complete book (whole text) full work

Below is the text of the book, divided by pages. System saving the place of the last page read, allows you to conveniently read the book "SQL for Data Scientists: A Beginners Guide for Building Datasets for Analysis" online for free, without having to search again every time where you left off. Put a bookmark, and you can go to the page where you finished reading at any time.

Light

Font size:

Reset

Interval:

Bookmark:

Make
Table of Contents List of Tables Chapter 3 List of Illustrations Chapter - photo 1
Table of Contents
List of Tables
  1. Chapter 3
List of Illustrations
  1. Chapter 1
  2. Chapter 2
  3. Chapter 3
  4. Chapter 4
  5. Chapter 5
  6. Chapter 6
  7. Chapter 7
  8. Chapter 8
  9. Chapter 9
  10. Chapter 10
  11. Chapter 11
  12. Chapter 12
  13. Chapter 13
  14. Chapter 14
Guide
Pages

SQL for Data Scientists A Beginners Guide for Building Datasets for Analysis - photo 2

SQL for Data Scientists
A Beginner's Guide for Building Datasets for Analysis

Rene M. P. Teate

Copyright 2021 by John Wiley Sons Inc All rights reserved Published by - photo 3

Copyright 2021 by John Wiley & Sons, Inc. All rights reserved.

Published by John Wiley & Sons, Inc., Hoboken, New Jersey.
Published simultaneously in Canada.

ISBN: 978-1-119-66936-4
ISBN: 978-1-119-66937-1 (ebk)
ISBN: 978-1-119-66939-5 (ebk)

No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, (978) 750-8400, fax (978) 750-4470, or on the web at www.copyright.com. Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, (201) 748-6011, fax (201) 748-6008, or online at http://www.wiley.com/go/permission.

Limit of Liability/Disclaimer of Warranty: While the publisher and author have used their best efforts in preparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives or written sales materials. The advice and strategies contained herein may not be suitable for your situation. You should consult with a professional where appropriate. Neither the publisher nor author shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages.

For general information on our other products and services or for technical support, please contact our Customer Care Department within the United States at (800) 762-2974, outside the United States at (317) 572-3993 or fax (317) 572-4002.

Wiley also publishes its books in a variety of electronic formats. Some content that appears in print may not be available in electronic formats. For more information about Wiley products, visit our web site at www.wiley.com.

Library of Congress Control Number: 2021941400

Trademarks: WILEY and the Wiley logo are trademarks or registered trademarks of John Wiley & Sons, Inc. and/or its affiliates, in the United States and other countries, and may not be used without written permission. All other trademarks are the property of their respective owners. John Wiley & Sons, Inc. is not associated with any product or vendor mentioned in this book.

Cover image: filo/Getty Images
Cover design: Wiley

In my data science career talks, I warn about tech industry gatekeepers.
This book is dedicated to the gate-openers
.

About the Author

Rene 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.

Rene 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 shes 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.

About the Technical Editor

Vicki Boykis is a machine learning engineer, currently working with recommendation systems. She has over a decade of experience in analytics and databases across numerous industries including social media, telecom, and healthcare, and has worked with Postgres, SQL Server, Oracle, and MySQL. She has previously taught courses in object-oriented programming (OOP) for Python and MySQL for massive open online courses (MOOCs). She has a BS in Economics with Honors from Penn State University and an MBA from Temple University in Philadelphia.

Acknowledgments

When I first started this book in Fall 2019, I was new to the book authoring and publication process, and I couldnt have anticipated how everything around us would change due to a deadly pandemic and political upheaval. I want to first acknowledge the healthcare and other essential workers who risked their lives during this era of COVID-19. Nothing any of us have accomplished throughout this time would have been possible without your selfless efforts saving lives and allowing some of us to work safely from home. I also want to thank those who continue fighting for equality in the face of injustice. You inspire me and give me hope.

As a first-time book author, the process of transferring my knowledge and experience to the page, and bringing this book to completion, has been a major learning experience. I would like to thank the team at Wiley for taking the chance on me and for all of your work, especially project editor Kelly Talbot for guiding me through this process, improving my content, and eventually getting me across the finish line!

I was so excited when I found out that Vicki Boykis, whose writing about our industry is fascinating and insightful, would be my technical editor. Her thoughtful feedback was invaluable. I truly appreciate her sticking with me throughout this extended process.

I would also like to thank my family and teachers, who encouraged my interest in computers and technology from a young age and fostered my love of reading, and my friends and mentors who have helped me continue to progress in my education and my career since. Those who have had an impact on me are too numerous to list, but know that I acknowledge your role in helping me get to where I am today. My parents and sister, my husband and step-children, my teachers and managers, my colleagues and friends, your time and energy and patience is so appreciated.

And I want to give heartfelt thanks to my husband and my step-son, Tony and Anthony Teate, for always believing in me, giving invaluable feedback, and bearing with me during this extended project. Tony has been a vital part of my data science journey from the very beginning, and Im fittingly wrapping up this long phase of it on his birthday (Happy Birthday, Sweetheart!). The love and support the two of you have shown me is beyond measure. I love you.

Next page
Light

Font size:

Reset

Interval:

Bookmark:

Make

Similar books «SQL for Data Scientists: A Beginners Guide for Building Datasets for Analysis»

Look at similar books to SQL for Data Scientists: A Beginners Guide for Building Datasets for Analysis. We have selected literature similar in name and meaning in the hope of providing readers with more options to find new, interesting, not yet read works.


Reviews about «SQL for Data Scientists: A Beginners Guide for Building Datasets for Analysis»

Discussion, reviews of the book SQL for Data Scientists: A Beginners Guide for Building Datasets for Analysis and just readers' own opinions. Leave your comments, write what you think about the work, its meaning or the main characters. Specify what exactly you liked and what you didn't like, and why you think so.