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The Applied SQL Data Analytics Workshop

The Applied SQL Data Analytics Workshop - Second Edition

By : Matt Goldwasser , Upom Malik , Benjamin Johnston
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The Applied SQL Data Analytics Workshop

The Applied SQL Data Analytics Workshop

4 (4)
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)
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Preface
7
7. The Scientific Method and Applied Problem Solving

1. Introduction to SQL for Analytics

Activity 1.01: Classifying a New Dataset

Solution

  1. The unit of observation is a car sale.
  2. Date and Sales Amount are quantitative, while Make is qualitative.
  3. While there could be many ways to convert Make into quantitative data, one commonly accepted method would be to map each of the Make types to a number. For instance, Ford could map to 1, Honda could map to 2, Mazda could map to 3, Toyota could map to 4, Mercedes could map to 5, and Chevy could map to 6.

Activity 1.02: Exploring Dealership Sales Data

Solution

  1. Open Microsoft Excel to a blank workbook.
  2. Go to the Data tab and click on From Text.
  3. Find the path to the dealerships.csv file and click on OK.
  4. Choose the Delimited option in the Text Import Wizard dialog box and make sure that you start the import at row 1. Now, click on Next.
  5. Select the delimiter for your file. As this file is only one column, it has no delimiters, although CSVs traditionally...
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The Applied SQL Data Analytics Workshop
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