🗄️ SQL Important Tips for Beginners — Part 2

If you're learning SQL for Data Analytics, don't just memorize syntax. Focus on understanding how to write correct queries and how SQL processes your data.

📌 1. Always Understand the Question First

Before writing SQL, identify:

• What information is required?

• Which table contains the data?

• Which columns are needed?

• Do you need filtering?

• Do you need grouping?

• Do you need a JOIN?

Understanding the problem first makes writing the query much easier.

📌 2. Use WHERE to Filter Rows

WHERE is used to filter individual records.

SELECT *
FROM employees
WHERE department = 'IT';

Think:

WHERE → Which rows do I need?

📌 3. Remember WHERE vs HAVING

This is one of the most common SQL interview questions.

WHERE → Filters rows before grouping

HAVING → Filters groups after aggregation

SELECT department, COUNT(*) AS employee_count
FROM employees
GROUP BY department
HAVING COUNT(*) > 10;

📌 4. Be Very Careful with JOINs

JOINs are extremely important for Data Analysts.

Before joining tables, understand:

• Primary key

• Foreign key

• One-to-one relationship

• One-to-many relationship

• Many-to-many relationship

A wrong JOIN can produce incorrect results and duplicate records.

📌 5. Understand INNER JOIN vs LEFT JOIN

Remember the basic idea:

INNER JOIN → Returns matching records from both tables.

LEFT JOIN → Returns all records from the left table and matching records from the right table.

This simple concept will help you solve many interview questions.

📌 6. Always Check for Duplicate Rows After a JOIN

If you expected 1,000 rows but your JOIN produces 10,000 rows, don't immediately use DISTINCT.

First investigate whether the JOIN relationship is causing multiple matches.

📌 7. Master GROUP BY

GROUP BY is essential for data analysis.

SELECT department, SUM(salary) AS total_salary
FROM employees
GROUP BY department;

Think:

GROUP BY → How do I want to summarize my data?

📌 8. Learn Aggregate Functions Properly

Master these functions:

• COUNT()

• SUM()

• AVG()

• MIN()

• MAX()

Practice them with GROUP BY and HAVING.

📌 9. Don't Forget NULL

NULL means missing or unknown value.

Incorrect:

WHERE salary = NULL

Correct:

WHERE salary IS NULL

Also learn:

• COALESCE()

• NULLIF()

📌 10. Learn CASE WHEN

CASE WHEN is extremely useful for creating business categories.

CASE
    WHEN salary >= 100000 THEN 'High'
    WHEN salary >= 50000 THEN 'Medium'
    ELSE 'Low'
END

You'll use it frequently in real-world analytics.

📌 11. Don't Overuse DISTINCT

DISTINCT removes duplicate results.

But if you're using DISTINCT because your JOIN unexpectedly created duplicates, investigate the JOIN instead.

📌 12. Learn Date Functions

Data Analyst interviews frequently involve dates.

Practice questions involving:

• Year

• Month

• Quarter

• Date difference

• Month-over-month growth

• Year-over-year growth

• Rolling periods

Date-based SQL problems are extremely common in analytics.

📌 13. Start Learning Window Functions

Once you're comfortable with basic SQL, learn:

• ROW_NUMBER()

• RANK()

• DENSE_RANK()

• LAG()

• LEAD()

• SUM() OVER()

• AVG() OVER()

These are extremely important for Data Analyst interviews.

📌 14. Understand RANK vs DENSE_RANK

For example, if salaries are:

100000

100000

90000

80000

RANK() gives:

1

1

3

4

DENSE_RANK() gives:

1

1

2

3

This difference is frequently tested in interviews.

📌 15. Use CTEs for Complex Queries

Instead of writing one huge query, break the logic into smaller steps using a CTE.