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 order to extract insights from your database, you need data. And, while many companies store and update data within a central database, there are scenarios in which you will need more data than is currently in your database. In this chapter, we are going to explore how we can efficiently upload data to our centralized database for further analysis.

Not only will we want to upload data to our database for further analysis, but if we are doing advanced analytics, there will also be situations wherein we will need to download data from our database (for example, if we want to perform a statistical analysis that is unavailable in SQL). For this reason, we will also explore the process of extracting data from our database. This will allow you to use other software to analyze your data.

In this chapter, we will look at how you can integrate your workflows with two specific programming languages that are frequently used for analytics: Python and R. These languages are...