SQL OPERATOR WEEK 2 21ST-22ND NOVEMBER

Eunice Sashq — Wed, 28 Oct 2026 19:10:38 +0000

SQL (Structured Query Language) allows communication with databases to facilitate easy extraction and manipulation of data. Data Query Language (DQL) is a sublanguage in SQL that lets us filter, organize, and retrieve specific data based on a given condition. The SELECT keyword forms the foundation of querying and data extraction. When using SELECT, we are not creating new tables; we are just temporarily retrieving read-only data based on requested results.
Basic query syntax is:
The FROM keyword always specifies which table to query.

SELECT * retrieves data from all available columns in the table.

LIMIT restricts the number of rows returned by a query.
Filtering & Operators
The WHERE clause is used to retrieve data conditionally and filter data where a specific condition is met or true.

It is used alongside comparison operators to determine whether a condition is true or false:

Equals (=)

Not equal to (<> or !=)

Less than (<)

Greater than (>)

Less than or equal to (<=)

Greater than or equal to (>=)
Removing Duplicates
SELECT DISTINCT eliminates rows where data is duplicated or exact duplicates exist.

It does not change the original table in the database; it only affects the query results by returning unique values.
Aliasing uses the AS keyword to temporarily rename a table or column in a query for easy readability and simplification.

Syntax: SELECT col_name AS new_col_name FROM db.table;.

Always use descriptive names while aliasing
To save query results in the database without interfering with the original dataset, we create a new table first, then insert the query results into it.
Example:
CREATE TABLE No_Duplicates (name VARCHAR, age INT);
SELECT DISTINCT name, age FROM company.employees;
INSERT INTO No_Duplicates (name, age);
Combining Conditions with Logical Operators (AND, OR, NOT)
Often, a single condition isn't specific enough. This is where logical operators come in:

AND-Returns records only if all conditions separated by AND are true.
OR- Returns records if at least one of the conditions is true.
NOT- Reverses the result of the condition (excludes matches).
Working with Ranges and Lists (BETWEEN and IN)
Writing multiple OR statements can make your queries messy. SQL provides cleaner shorthand tools for ranges and lists:

BETWEEN-Filters data within a specific range (inclusive of the boundary values).
IN- Checks if a column matches any value inside a specified list.
Dealing with Missing Data (IS NULL and IS NOT NULL)
In data science and database administration, missing or incomplete data is a daily hurdle. In SQL, missing data is represented by NULL.
You cannot use standard comparison operators like = to find NULL values (more on that in the mistakes section!). Instead, you must use IS NULL or IS NOT NULL.
Text Pattern Matching with LIKE
Exact matches are helpful, but what if you only remember part of a patient's name or a drug code? The LIKE operator allows you to search for patterns using wildcards:

% represents zero, one, or multiple characters.
_ represents a single character.
Common Mistakes to Avoid
Every beginner runs into these roadblocks when starting out with SQL filtering. Keep these in mind to save yourself hours of debugging:

i)Using = NULL instead of IS NULL: Because NULL represents the absence of a value, writing WHERE column = NULL will always evaluate to unknown and return zero rows. Always use IS NULL or IS NOT NULL.

DEV Community: Eunice Sashq

SQL OPERATOR WEEK 2 21ST-22ND NOVEMBER