Book Image

SQL for Data Analytics

By : Upom Malik, Matt Goldwasser, Benjamin Johnston
3 (1)
Book Image

SQL for Data Analytics

3 (1)
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)
9
9. Using SQL to Uncover the Truth – a Case Study

Updating Tables

Over time, you may also need to modify a table by adding columns, adding new data, or updating existing rows. We will discuss how to do that in this section.

Adding and Removing Columns

To add new columns to an existing table, we use the ADD COLUMN statement as in the following query:

ALTER TABLE {table_name}
ADD COLUMN {column_name} {data_type};

Let's say, for example, that we wanted to add a new column to the products table that we will use to store the products' weight in kilograms called weight. We could do this by using the following query:

ALTER TABLE products
ADD COLUMN weight INT;

This query will make a new column called weight in the products table and will give it the integer data type so that only numbers can be stored within it.

If you want to remove a column from a table, you can use the DROP column statement:

ALTER TABLE {table_name}
DROP COLUMN {column_name};

Here, {table_name} is the name of the table you want to...