Filtering Data using SQL Queries

In the SQL Essentials guide, the section on Filtering under Basic SQL Queries plays a crucial role in understanding how to extract specific information from a database. This section provides valuable insights into filtering records based on particular criteria, a fundamental skill for any aspiring SQL developer. Let’s delve into the content based on the provided SQL queries:

1. Distinct Order Statuses

To analyze the distinct order statuses within an ‘orders’ table, the SQL query utilizes the DISTINCT keyword. This command is instrumental in retrieving unique values from the order_status column, eliminating any duplicates. By ordering the results based on the first column, which in this case is the distinct order_status, the output is neatly organized for easier analysis.

Query:

SELECT DISTINCT order_status FROM orders
ORDER BY 1;

This query is particularly useful for obtaining a clear picture of all possible order statuses in the system without sifting through redundant entries.

2. Complete Order Status Filter

To focus on orders that have been marked as ‘COMPLETE’, the following query filters the dataset to include only those specific records. This filtration is essential for scenarios where completed orders require further processing or analysis.

Query:

SELECT * FROM orders
WHERE order_status = 'COMPLETE';

By selecting all columns for orders in the ‘COMPLETE’ status, users can perform detailed evaluations or extract comprehensive data regarding completed transactions.

3. Closed Order Status Filter

Similar to the previous filter but targeting a different status, this query retrieves all orders labeled as ‘CLOSED’. This operation is vital for assessing all orders that are no longer active or subject to further changes.

Query:

SELECT * FROM orders
WHERE order_status = 'CLOSED';

Understanding closed orders can help in post-mortem analyses or in confirming that no further action is required on these orders.

4. Closed or Complete Order Status Filter

Combining the conditions from the earlier examples, this query aims to extract orders that are either ‘CLOSED’ or ‘COMPLETE’. It demonstrates the use of the OR logical operator to broaden the search criteria.

Query:

SELECT * FROM orders
WHERE order_status = 'CLOSED' OR order_status = 'COMPLETE';

This consolidated view is particularly useful when tasks or analyses need to encompass all orders that are no longer in progress.

5. Using the IN Operator for Filtering

An alternative to the previous query that uses the IN operator, this command achieves the same result but with more concise syntax. The IN operator allows for specifying multiple values within a single condition, making the query easier to read and maintain.

Query:

SELECT * FROM orders
WHERE order_status IN ('CLOSED', 'COMPLETE');

This method is efficient for checking against multiple potential values of order_status and is exemplary for demonstrating how to streamline SQL queries without sacrificing functionality.

By mastering these queries, users can enhance their ability to interact with and analyze SQL databases, extracting precise datasets based on dynamic requirements.

Keep in mind that regular practice is key to mastering SQL. Engage actively with SQL by experimenting across diverse scenarios, delve into various data sets, explore a range of functions and clauses, and embrace different challenges to deepen your understanding.


Furthermore, enhance your learning by diving into SQL, Python, Hadoop, Spark, and more with our cutting-edge Big Data Cluster. When you sign up for our labs, you not only gain access to state-of-the-art technology but also receive dedicated support from our team. This support is integral for navigating Data Engineering courses, helping you overcome any challenges and deepening your expertise in the field.