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SQL for Data Analytics

SQL for Data Analytics

By : Upom Malik , Matt Goldwasser , Benjamin Johnston
3.5 (35)
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SQL for Data Analytics

SQL for Data Analytics

3.5 (35)
By: Upom Malik , Matt Goldwasser , Benjamin Johnston

Overview of this book

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.
Table of Contents (11 chapters)
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9
9. Using SQL to Uncover the Truth – a Case Study
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Introduction

Throughout SQL for Data Analytics, you have learned a range of new skills, including basic descriptive statistics, SQL commands and importing and exporting data in PostgreSQL, as well as more advanced methods, such as functions and triggers. In this final chapter of the book, we will combine these new skills with the scientific method and critical thinking to solve the real-world problem of understanding the cause of an unexpected drop in sales. This chapter provides a case study and will help you to develop confidence in applying your new SQL skillset to your own problem domains. To solve the problem presented in this use case, we will use the complete range of your newly developed skills, from using basic SQL searches to filter out the available information to aggregating and joining multiple sets of information and using windowing methods to group the data in a logical manner. By completing case studies such as this, you will refine one of the key tools in your data...

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SQL for Data Analytics
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