SQL

Why is SQL important for data scientists?

Data scientists use SQL to analyze and process large amounts of data in relational databases. SQL gives them the ability to extract data efficiently to transform and load (ETL)to create data models, formulate complex queries and visualize the results.

It is used to store, read, update, and delete data, as well as to create complex queries to extract information from the data.

SQL is an essential tool for analysts and scientists working with relational databases. Mastering SQL enables them to efficiently analyze and process data and gain valuable insights from it.

What are basic SQL commands?

• SELECT: This command is used to retrieve data from one or more tables.
• FROM: This command specifies the table from which the data is to be retrieved.
• WHERE: This command allows you to filter results based on specific criteria.
• ORDER BY: This command sorts the results by one or more columns.
• LIMIT: This command limits the number of rows returned.

Examples for SQL-Queries

Show all customers from Germany:

• SQL
‍‍SELECT * FROM customers WHERE country = 'Deutschland';

The ten products with the most revenue:

• SQL
SELECT product_name, revenue
FROM products
ORDER BY revenue DESC
LIMIT 10;
  

Average order size by customer:

• SQL
SELECT customer_id, AVG(order_amount) AS average_order_amount
FROM orders
GROUP BY customer_id;

SQL learning resources

• W3Schools SQL Tutorial: https://www.w3schools.com/sql/
• SQLZoo: https://sqlzoo.net/
• DataCamp SQL course: https://www.datacamp.com/learn/sql
• Khan Academy SQL Tutorial: https://www.khanacademy.org/computing/computer-programming/sql

Additional information about SQL

SQL is a standardized language, meaning it can be used with various relational databases. There are various extensions and dialects of SQL, ranging from specific  databases are offered. In addition to basic syntax, SQL also provides advanced features such as joins, subqueries, and window functions.

The article focuses on data scientists because SQL is a particularly important skill for this profession. Data scientists often work with relational databases to extract, transform, and analyze data. SQL is the basic language used to access and process this data.

However, are databases and SQL is also relevant in other areas, for example:

• Business intelligence analysts: They use data to understand and improve a company's performance. SQL helps them get relevant data from  databases to draw.
• Database administrators: They manage and maintain databases, including writing queries using SQL.
• Developers: Databases are involved in many development projects, so developers must work with SQL to interact with them.

In summary: While SQL is particularly important for data scientists, it is also used in other areas that work with data and databases.

Note: Our team benefited from the support of AI technologies while creating and maintaining this glossary.