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SQL: Standardizing and Transforming Data

Standardizing and transforming data in SQL involves manipulating the data to meet certain standards or requirements. This typically includes tasks like converting data types, cleaning data, normalizing or denormalizing data, and performing calculations or aggregations. Below are some common techniques for standardizing and transforming data in SQL:

Data Type Conversion: Convert data from one type to another using functions like CAST or CONVERT.

SELECT CAST(column_name AS new_data_type) AS new_column_name

FROM table_name;

Cleaning Data: Remove duplicates, handle missing values, and correct errors in data.

DELETE FROM table_name WHERE column_name IS NULL;

String Manipulation: Modify string values using functions like CONCAT, SUBSTRING, UPPER, LOWER, etc.

SELECT CONCAT(first_name, ' ', last_name) AS full_name FROM table_name;

Date Manipulation: Extract parts of a date, perform arithmetic operations, or format dates using functions like DATEPART, DATEADD, DATEDIFF, FORMAT, etc.

SELECT DATEPART(year, date_column) AS year

FROM table_name;

Normalization and Denormalization: Normalize data into multiple tables to reduce redundancy or denormalize data by combining multiple tables into one for easier querying.

-- Normalization

CREATE TABLE customers (

    customer_id INT PRIMARY KEY,

    customer_name VARCHAR(100)



    order_id INT PRIMARY KEY,

    customer_id INT,

    order_date DATE,

    FOREIGN KEY (customer_id) REFERENCES customers(customer_id)


-- Denormalization

SELECT customers.customer_name, orders.order_date

FROM customers

JOIN orders ON customers.customer_id = orders.customer_id;

Aggregations: Perform calculations on groups of data using aggregate functions like SUM, AVG, MIN, MAX, etc.

SELECT category, SUM(revenue) AS total_revenue

FROM sales

GROUP BY category;

Case Statements: Conditionally transform data based on specific criteria using CASE statements.




        WHEN condition1 THEN result1

        WHEN condition2 THEN result2

        ELSE result3

    END AS transformed_column

FROM table_name;

These are just a few examples of how you can standardize and transform data in SQL. Depending on your specific requirements and the capabilities of your SQL database, there may be additional techniques and functions available for data transformation.

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