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

Date and Time Data types for Analysis

You may be familiar with dates and times, but do you know how these quantitative measures are represented? They are represented using numbers, but not a single number. Instead, they are measured with a set of numbers, with one number each for year, month, day, hour, minute, second, and millisecond.

This is a complex representation, comprising several different components. For example, knowing the current minute without knowing the current hour does not serve any purpose. Additionally, there are complex ways of interacting with dates and times; for example, different points in time can be subtracted from one another. The current time can be represented differently depending on where you are in the world.

As a result of these intricacies, you need to take special care when working with this type of data. In fact, PostgreSQL, like most databases, offers special data types that can represent these types of values. You will start by examining...