Book Image

SQL for Data Analytics - Third Edition

By : Jun Shan, Matt Goldwasser, Upom Malik, Benjamin Johnston
Book Image

SQL for Data Analytics - Third Edition

By: Jun Shan, Matt Goldwasser, Upom Malik, Benjamin Johnston

Overview of this book

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.
Table of Contents (11 chapters)
9. Using SQL to Uncover the Truth: A Case Study

Data Analytics and Statistics

Raw data is a group of values that you can extract from a source. It becomes useful when it is processed to find different patterns in the data that was extracted. These patterns, also referred to as information, help you to interpret the data, make predictions, and identify unexpected changes in the future. This information is then processed into knowledge.

Knowledge is a large, organized collection of persistent and extensive information and experience that can be used to describe and predict phenomena in the real world. Data analysis is the process by which you convert data into information and, thereafter, knowledge. Data analytics is when data analysis is combined with making predictions.

There are several data analysis techniques available to make sense of data. One of them is statistics, which uses mathematical techniques on datasets.

Statistics is the science of collecting and analyzing a large amount of data to identify the characteristics...