Jay Potter Sep 20, 2022

“SQL for Data Analytics” is an excellent book that is beneficial for both a new SQL learner as well as providing helpful guidance for more knowledgeable SQL users. It would work well in the classroom setting, as well as for an individual learning on their own.I appreciate that this text starts before the use of SQL for gaining a broader understanding of data and relevant statistic concepts. Each chapter begins with an overview and ends with a summary, which really helps the reader to understand where they are going next and how the concepts build upon one another. The text does not leave you wondering where you are in the process of learning SQL. It provides relevant examples that build along with the lessons, all the way up to a case study that rounds out all of the knowledge from the earlier lessons.I recommend this title for anyone wanting to learn more about SQL, whether you are in a class with others, or learning on your own, it will be of great service to your learning as you follow along with the concepts and examples.My only caveat about this book is that some of the software versions that they give examples from and instruction on how to use are a few years old, with a few slight variations due to upgrades. They do provide step-by-step instruction on downloading and using these programs for Windows, Mac, and Linux, which is very helpful, but do note that some parts may be slightly different if you have a newer version of a program or operating system.I received this copy of “SQL for Data Analytics” in return for writing this review, this in no way shaped my thoughts on this book. As a former professor and current practitioner in data analysis and SQL I recommend this book regardless.

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Martin Melgar Oct 25, 2022

An excellent and insightful look into SQL. This book is easily digestible and the authors give very concise and easy to follow instructions on both setting up the PostGres server as well as giving great exercises to follow that one can upload to their own GitHub to show experience. I highly recommend this for anyone who wants to start learning SQL or anyone who wishes to practice their SQL skills more in depth.- Martin

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Sahil Sep 15, 2022

Lots of great material here laid out in an easy to digest format. Especially appreciate the focus of the last chapters on optimizing SQL queries and the case study.

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J.P.G. Apr 23, 2023

SQL for Data Analytics is a comprehensive and practical guide for anyone interested in becoming a data analyst or improving their SQL skills. The book is structured in a way that allows you to learn SQL concepts and apply them to actual real-world scenarios.I was impressed with the book's approach to data analysis, starting with how to form hypotheses and generate related statistics, and then progressing to advanced statistical calculations and techniques. The author has done a great job of making even the most complex concepts easy to understand, with clear explanations and practical examples.What I appreciated most about this book was the emphasis on hands-on learning. The practical exercises and activities throughout the book help you master each concept and apply what you've learned in a real-world setting. The case study at the end of the book is particularly helpful, as it allows you to use all the techniques you've learned in a single project.The book assumes no prior knowledge of SQL, and it's written in a way that's accessible to beginners as well. Even if you're an experienced SQL user, you'll find techniques that you can apply to your work.Overall, I highly recommend SQL for Data Analytics to anyone interested in data analysis or looking to improve their SQL skills. The book is engaging, informative, and practical, and it's a great addition to your professional toolkit!

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Mrs. Campbell Sep 27, 2022

The book SQL for Data Analytics, Third Edition is a great resource for beginners who have had some basic exposure to SQL and intermediate to high level users alike and covers a wide range of use of this versatile data retrieval and manipulation language. For anyone looking to have a career in data analytics/analysis, SQL is a must-have and in-demand skill so having the right foundational knowledge of the different ways to use it is key.The beginning chapter gives a quick, broad level overview of the data analytics, data analysis, statistics, and working with data sets. Some of the topics could be its own book in and of itself; but the authors did a good job of giving a high level overview and resultant mini-exercises to reinforce the readers’ understanding of them. This chapter does not go into the SQL language just yet but prepares the reader for the types of analysis they will be doing with it.The next chapters focus on the syntax and structure of making SQL queries. Basics such as the SELECT statement, etc are covered in good detail with sample exercises given using a PostgreSQL working environment which they ask you to install on your computer. It also goes over CRUD functions and concepts such as case when, aggregate functions and other helpful statements that most people will use with SQL. The exercises are lined up perfectly after a concept is introduced in order to reinforce them. I appreciated some of the minute details and tips such as how to determine whether every value in a column is unique and other helpful query examples that one might run into in your day to day business needs.After the chapter on Window functions, which is a more intermediate use case, the book goes into concepts that are more advanced in nature and will be appreciated by more veteran analysts such as using python to read/write data in your database using pandas and working with more complex data types such as geospatial, array, and JSON. It also goes over tips and techniques on how to make your SQL more efficient and ends with a case study that the reader can then draw from all the skills learned in the book.The book is very thorough in showing how versatile SQL can be - maybe a little too thorough in some regards. For example, the section on text analytics is very appreciated (I personally was not aware of being able to tokenize text in SQL). However, for most data folks I believe other languages such as R and Python are preferred to conduct text analytics.Overall, I highly recommend this book as it speaks to both data analysts or scientists alike with a wide range of abilities in trying to optimize their understanding of SQL alongside real-world business use cases.

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SQL for Data Analytics: Harness the power of SQL to extract insights from data , Third Edition

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