Read and navigate any database table

To communicate with a database, we use a language called SQL (Structured Query Language). Instead of telling the database step by step how to find data, you simply describe what you want, and the database figures out the rest. SQL is designed to be human-readable, using words like SELECT and FROM that describe your request in plain English.

Pull specific columns from any table

A query is a question; it is a request for the database to retrieve some data in the format that you specify, and show you the results. Every query needs three things: the keyword SELECT, a list of columns you want to see, and the keyword FROM. Think of SELECT as the request, the column list as your shopping list, and FROM as the aisle where the database finds what you asked for.

A query always starts with SELECT. It tells the database to return data. Everything listed after SELECT describes which pieces of that data you want to see.

After SELECT, list each column you want, separated by commas. The database returns exactly those columns, in the order you listed them.

FROM names the table to query. Databases contain many tables, so naming the right one tells the database exactly where to look for the data you requested.

Every SQL query starts with SELECT and ends with the table name after FROM. This ordering is fixed: SELECT declares what data you want, and FROM declares where to find it.

When selecting multiple columns, list each name after SELECT separated by commas: SELECT name, age FROM users. The database returns only the columns you listed, in the order you listed them.

___
  name,
  age
___ users

The column list after SELECT is your contract with the database: you are saying exactly which pieces of information matter for this particular question.

Writing SELECT and FROM in uppercase is a convention that makes SQL easier to scan, separating the SQL keywords from the table and column names you supply.

Pull complete datasets with one keyword

If you want to see every column in a table, you can use the * symbol instead of listing each column. This is handy when you are exploring a new table.

Knowing when to use SELECT * versus named columns helps you write efficient, readable queries.

In practice, the columns you select depend on the question you're trying to answer. A marketing team asking "who are our customers?" needs name and country. A finance team asking "what do things cost?" needs product_name and price. The same database can answer very different questions depending on which columns you choose.

SELECT
  ___,
  ___
FROM products

In production systems, SELECT * can cause pipelines to break if a new column is added to a table, because downstream code may not expect it. Named columns are more robust.

Rename columns for clearer results

SQL supports two types of aliases using the AS keyword. Column aliases let you rename columns in your results, making the output more readable. Table aliases create shorthand names for tables, which is helpful when working with long table names or multiple tables.

SELECT
  email ___ ___
FROM users

Table aliases are used most often when writing JOIN queries, where two tables may have columns with the same name and the alias helps clarify which table each column comes from.

Calculate new values inside your query

SELECT
  quantity ___ ___ AS total_cost
FROM orders

Adding an AS alias to every expression in your SELECT list ensures the output column has a meaningful name instead of the literal formula text, which makes results easier to read.