Book Image

The Applied SQL Data Analytics Workshop - Second Edition

By : Matt Goldwasser, Upom Malik, Benjamin Johnston
3.5 (2)
Book Image

The Applied SQL Data Analytics Workshop - Second Edition

3.5 (2)
By: 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. Hidden in this data are key patterns and behaviors that can help you and your business understand your customers at a deep, fundamental level. Are you ready to enter the exciting world of data analytics and unlock these useful insights? Written by a team of expert data scientists who have used their data analytics skills to transform businesses of all shapes and sizes, The Applied SQL Data Analytics Workshop is a great way to get started with data analysis, showing you how to effectively sieve and process information from raw data, even without any prior experience. The book begins by showing you how to form hypotheses and generate descriptive statistics that can provide key insights into your existing data. As you progress, you'll learn how to write SQL queries to aggregate, calculate and combine SQL data from sources outside of your current dataset. You'll also discover how to work with different data types, like JSON. By exploring advanced techniques, such as geospatial analysis and text analysis, you'll finally 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 The Applied SQL Data Analytics Workshop, you'll have the skills you need to start identifying patterns and unlocking insights in your own data. You will be capable of looking and assessing data with the critical eye of a skilled data analyst.
Table of Contents (9 chapters)
Preface
7
7. The Scientific Method and Applied Problem Solving

Introduction

In the previous chapter, we learned how to import and export data into other analytical tools in order to leverage analytical tools outside of our database. It is often easiest to analyze numbers; however, in the real world, data is frequently found in other formats, such as words, locations, dates, and, sometimes, complex data structures. In this chapter, we will look at these other formats and examine how we can use this data in our analysis.

First, we will look at commonly found column types: the latitude, and longitude columns. These data types will give us a foundational understanding of our data from both a temporal and a geospatial perspective. Next, we will look at complex data types, such as arrays and JSON, and learn how to extract data points from these complex data types. These data structures are often used for alternative data, or log-level data, such as website logs. Finally, we will look at how we can extract meaning out of text in our database and use...