Book Image

The SQL Workshop

By : Frank Solomon, Prashanth Jayaram, Awni Al Saqqa
Book Image

The SQL Workshop

By: Frank Solomon, Prashanth Jayaram, Awni Al Saqqa

Overview of this book

Many software applications are backed by powerful relational database systems, meaning that the skills to be able to maintain a SQL database and reliably retrieve data are in high demand. With its simple syntax and effective data manipulation capabilities, SQL enables you to manage relational databases with ease. The SQL Workshop will help you progress from basic to advanced-level SQL queries in order to create and manage databases successfully. This Workshop begins with an introduction to basic CRUD commands and gives you an overview of the different data types in SQL. You'll use commands for narrowing down the search results within a database and learn about data retrieval from single and multiple tables in a single query. As you advance, you'll use aggregate functions to perform calculations on a set of values, and implement process automation using stored procedures, functions, and triggers. Finally, you'll secure your database against potential threats and use access control to keep your data safe. Throughout this Workshop, you'll use your skills on a realistic database for an online shop, preparing you for solving data problems in the real world. By the end of this book, you'll have built the knowledge, skills and confidence to creatively solve real-world data problems with SQL.

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Table of Contents (13 chapters)
Preface
Preface
About the Book
About the Chapters
Free Chapter
1
1. SQL Basics
1. SQL Basics
Introduction
Understanding Data
An Overview of Basic SQL Commands
Data Types in SQL
Creating Simple Tables
Populating Your Tables
Summary
2
2. Manipulating Data
2. Manipulating Data
Introduction
The INSERT Operation
The DELETE Operation
The ALTER Operation
The UPDATE Operation
Summary
3
3. Normalization
3. Normalization
Introduction
Primary Key Constraints
Foreign Key Constraints
Preserving Data Integrity
Types of Data Integrity
The Concept of Normalization
First Normal Form (1NF)
Second Normal Form (2NF)
Third Normal Form (3NF)
Denormalization
Summary
4
4. The SELECT Statement
4. The SELECT Statement
Introduction
Retrieving All Columns of a Table
Summary
5
5. Shaping Data with the WHERE Clause
5. Shaping Data with the WHERE Clause
Introduction
The WHERE Clause Syntax
The Not Equal Operator
Checking for NULLS
Combining Conditions with the AND, OR, and NOT Operators
Summary
6
6. JOINS
6. JOINS
Introduction
INNER JOIN
RIGHT JOIN
LEFT JOIN
CROSS JOIN
UNION JOIN
Summary
7
7. Subqueries, Cases, and Views
7. Subqueries, Cases, and Views
Introduction
Subqueries
Case Statements
Views
Summary
8
8. SQL Programming
8. SQL Programming
Introduction
Programming for SQL Products – The Basics
Functions
Summary
9
9. Security
9. Security
Introduction
Access Control (Authorization)
Summary
10
10. Aggregate Functions
10. Aggregate Functions
Introduction
Aggregate Functions (SUM, COUNT, AVG, MIN, and MAX) and the GROUP BY Clause
The HAVING Clause
Summary
11
11. Advanced SQL
11. Advanced SQL
Introduction
String Functions
Transactions
Summary
Appendix
Appendix
1. SQL Basics
2. Manipulating Data
3. Normalization
4. The SELECT Statement
5. Shaping Data with the WHERE Clause
6. JOINS
7. Subqueries, Cases, and Views
8. SQL Programming
9. Security
10. Aggregate Functions
11. Advanced SQL
What Next?

Understanding Data

For most companies, storing and retrieving data is a day-to-day activity. Based on how data is stored, we can broadly classify data as structured or unstructured. Unstructured data, simply put, is data that is not well-organized. Documents, PDFs, and videos fall into this category—they contain a mixture of different data types (text, images, audio, video, and so on) that have no consistent relationship between them. Media and publishing are examples of industries that deal with unstructured data such as this.

In this book, our focus will be on structured data. Structured data is organized according to a consistent structure. As such, structured data can be easily organized into tables. Thanks to its consistent organization, working with structured data is easier, and it can be processed more effectively. Tables are collections of entities or tuples (rows) and attributes (columns).

For example, consider the following table:

Figure 1.1: An example student’s database table

Figure 1.1: An example student's database table

For each row, there is a clear relationship; a given student takes a particular subject and achieves a specific score in that subject. The columns are also known as fields, while the rows are known as records.

Data that is presented in tabular form can be stored in a relational database. Relational databases, as the name suggests, store data that has a certain relationship with another piece of data. A Relational Database Management System (RDBMS) is a system that's used to manage relational data. SQL works very well with relational data. Popular RDBMSs include Microsoft SQL Server, MySQL, and Oracle. Throughout this book, we will be working with MySQL. We can use various SQL commands to work with data in relational databases. We'll have a brief look at them in the next section.

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