Saturday, September 23, 2023

How do you insert a new record into a table?

 To insert a new record into a table in SQL, you can use the INSERT INTO statement. This statement allows you to specify the values you want to insert into the columns of the table.

The basic syntax for inserting a new record is as follows:

INSERT INTO table_name (column1, column2, ...) 
VALUES (value1, value2, ...);
  • INSERT INTO: Specifies that you want to insert data into a specific table.
  • table_name: The name of the table you want to insert data into.
  • (column1, column2, ...): Optionally, you can specify the columns into which you want to insert data. If you omit this part, you need to provide values for all columns in the same order as they appear in the table.
  • VALUES (value1, value2, ...): Specifies the values you want to insert into the specified columns. Make sure the order of values matches the order of columns (or omit the column list, and the values should be provided for all columns in the same order as they appear in the table).

Here's an example of how to use the INSERT INTO statement to insert a new record into a table:

INSERT INTO customers (first_name, last_name, email, phone)
VALUES ('John', 'Doe', 'john.doe@example.com', '555-555-5555');

In this example, data is being inserted into the "customers" table. The values are provided for the "first_name," "last_name," "email," and "phone" columns.

If you want to insert data into all columns of a table, you can omit the column list and provide values for all columns in the same order as they appear in the table:

INSERT INTO products
VALUES ('12345', 'Example Product', 'Electronics', 49.99, 100);

In this case, data is inserted into all columns of the "products" table in the order: "product_id," "product_name," "category," "price," and "stock_quantity."

Make sure that the data you insert complies with the table's schema, including data types and constraints (e.g., primary keys, foreign keys, NOT NULL constraints). Incorrect or inconsistent data can result in errors or data integrity issues.

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