SQL for Data Analytics: Harness the power of SQL to extract insights from data, 3rd Edition 3rd ed. Edition
by Jun Shan，Matt Goldwasser，Upom Malik，Benjamin Johnston(Author)
Publisher finelybook 出版社: Packt Publishing; 3rd ed. edition (August 29, 2022)
Language 语言: English
Print Length 页数: 540 pages
ISBN-10: 180181287X
ISBN-13: 9781801812870
Book Description
By finelybook
Take your first steps to becoming a fully qualified data analyst by learning how to explore complex datasets
Key Features
Master each concept through practical exercises and activities
Discover various statistical techniques to analyze your data
Implement everything you’ve learned on a real-world case study to uncover valuable insights
Book Description
By finelybook
Every day, businesses operate around the clock, and a huge amount of data is generated at a rapid pace. This book helps you analyze this data and identify key patterns and behaviors that can help you and your business understand your customers at a deep, fundamental level.
SQL for Data Analytics, Third Edition is a great way to get started with data analysis, showing how to effectively sort and process information from raw data, even without any prior experience.
You will begin by learning how to form hypotheses and generate descriptive statistics that can provide key insights into your existing data. As you progress, you will learn how to write SQL queries to aggregate, calculate, and combine SQL data from sources outside of your current dataset. You will also discover how to work with advanced data types, like JSON. By exploring advanced techniques, such as geospatial analysis and text analysis, you will be able to understand your business at a deeper level. Finally, the book lets you in on the secret to getting information faster and more effectively by using advanced techniques like profiling and automation.
By the end of this book, you will be proficient in the efficient application of SQL techniques in everyday business scenarios and looking at data with the critical eye of analytics professional.
What you will learn
Use SQL to clean, prepare, and combine different datasets
Aggregate basic statistics using GROUP BY clauses
Perform advanced statistical calculations using a WINDOW function
Import data into a database to combine with other tables
Export SQL query results into various sources
Analyze special data types in SQL, including geospatial, date/time, and JSON data
Optimize queries and automate tasks
Think about data problems and find answers using SQL
Who this book is for
If you’re a database engineer looking to transition into analytics or a backend engineer who wants to develop a deeper understanding of production data and gain practical SQL knowledge, you will find this book useful. This book is also ideal for data scientists or business analysts who want to improve their data analytics skills using SQL.
Basic familiarity with SQL (such as basic SELECT, WHERE, and GROUP BY clauses) as well as a good understanding of linear algebra, statistics, and PostgreSQL 14 are necessary to make the most of this SQL data analytics book.
Table of Contents
1.Understanding and Describing Data
2.The Basics of SQL for Analytics
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
