Structured Query Language (SQL) plays a crucial role in data science as it allows us to interact with databases and extract valuable insights from large datasets. With SQL, we can efficiently perform tasks such as data retrieval, manipulation, and analysis.

Let's start by understanding the basics of SQL queries. SQL queries are used to retrieve specific data from a database. For example, to retrieve all the records from a table called 'Customers', we can use the query:

SELECT * FROM Customers;

This retrieves all the columns and rows from the 'Customers' table. SQL provides various other query types, including filtering, joining, sorting, and aggregating data that help us gain specific insights from the dataset.

Apart from queries, SQL also offers powerful features for database management. We can create, alter, and drop tables using SQL commands. For instance, to create a table called 'Orders', we can use the following command:

CREATE TABLE Orders (
  order_id INT PRIMARY KEY,
  customer_id INT,
  status VARCHAR(20)
);