Understanding and finding patterns in data has become one of the most important ways to improve business decisions. If you know the basics of SQL, but don't know how to use it to gain the most effective business insights from data, this book is for you.
SQL for Data Analytics helps you build the skills to move beyond basic SQL and instead learn to spot patterns and explain the logic hidden in data. You'll discover how to explore and understand data by identifying trends and unlocking deeper insights. You'll also gain experience working with different types of data in SQL, including time-series, geospatial, and text data. Finally, you'll learn how to increase your productivity with the help of profiling and automation.
By the end of this book, you'll be able to use SQL in everyday business scenarios efficiently and look at data with the critical eye of an analytics professional.
Please note: if you are having difficulty loading the sample datasets, there are new instructions uploaded to the GitHub repository. The link to the GitHub repository can be found in the book's preface.
publication date
2019-08-23
what you will learn
Perform advanced statistical calculations using the WINDOW function
Use SQL queries and subqueries to prepare data for analysis
Import and export data using a text file and psql
Apply special SQL clauses and functions to generate descriptive statistics
Analyze special data types in SQL, including geospatial data and time data
Optimize queries to improve their performance for faster results
Debug queries that won’t run
Use SQL to summarize and identify patterns in data
key features
Explore a variety of statistical techniques to analyze your data * Integrate your SQL pipelines with other analytics technologies * Perform advanced analytics such as geospatial and text analysis
approach
SQL for Data Analytics perfectly balances theory with practical implementation and provides a hands-on approach to analyzing data. Realistic exercises are used to demonstrate the implementation of statistical techniques so that you can better understand your data. Engaging activities that use real-life business scenarios allow you to practice and apply your new skills in a highly relevant context.
audience
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, 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. Knowledge of basic SQL and database concepts will aid in understanding the concepts covered in this book.
short description
SQL for Data Analytics teaches everything you need to know to progress from basic SQL to identifying trends and creating compelling narratives with data. With this book, you will be able to look at data with the critical eye of an analytics professional and extract meaningful insights that will improve your business.
subtitle
Perform fast and efficient data analysis with the power of SQL
keywords
SQL,Window function, Subqueries, Views, Temporary tables, database, Numeric Function, Date Function, Index scan, Sequential scan, Hash scan, JOIN, Killing queries, Datetime, Arrays,JSON, Text, Tokenization, Searching, Geospatial, COPY, SQLAlchemy
Product ISBN
9781789807356
