Top 10 SQL Queries Every Data Analyst Must Know

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If you can explain these with confidence, you are interview-ready

SQL interviews and day-to-day analytics work rarely test syntax alone. What matters is how you use queries to answer business questions.

This article covers 10 SQL queries every data analyst must know, explained with real-world examples, not textbook definitions.

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1. SELECT with WHERE — Filtering the Right Data

Why it matters:
Almost every analysis starts by narrowing data.

Query:

SELECT *
FROM Orders
WHERE OrderDate >= '2025-01-01';

Real-world use:
Analyze sales for the current year only.

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2. ORDER BY — Finding Top or Bottom Performers

Why it matters:
Business users often ask: Top customers? Worst products?

Query:

SELECT ProductName, SalesAmount
FROM Sales
ORDER BY SalesAmount DESC;

Example insight:
Identify the highest-selling product.

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3. GROUP BY with Aggregates — Business Summaries

Why it matters:
Executives don’t want raw data; they want summaries.

Query:

SELECT Region, SUM(SalesAmount) AS TotalSales
FROM Sales
GROUP BY Region;

Use case:
Regional performance dashboard.

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4. HAVING — Filtering Aggregated Results

Why it matters:
WHERE filters rows; HAVING filters groups.

Query:

SELECT Region, SUM(SalesAmount) AS TotalSales
FROM Sales
GROUP BY Region
HAVING SUM(SalesAmount) > 100000;

Business insight:
Regions contributing meaningful revenue.

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5. INNER JOIN — Combining Related Tables

Why it matters:
Real data lives in multiple tables.

Query:

SELECT c.CustomerName, o.OrderDate
FROM Customers c
INNER JOIN Orders o
ON c.CustomerID = o.CustomerID;

Use case:
Customer-wise order history.

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6. LEFT JOIN — Finding Missing Data

Why it matters:
Used to identify gaps, not just matches.

Query:

SELECT c.CustomerName
FROM Customers c
LEFT JOIN Orders o
ON c.CustomerID = o.CustomerID
WHERE o.CustomerID IS NULL;

Business question:
Which customers never placed an order?

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7. CASE WHEN — Business Logic in SQL

Why it matters:
Turns raw numbers into business-friendly categories.

Query:

SELECT SalesAmount,
       CASE
           WHEN SalesAmount >= 50000 THEN 'High'
           WHEN SalesAmount >= 20000 THEN 'Medium'
           ELSE 'Low'
       END AS SalesCategory
FROM Sales;

Use case:
Customer or product segmentation.

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8. Subquery — Step-by-Step Thinking

Why it matters:
Useful when logic needs to be broken into parts.

Query:

SELECT *
FROM Employees
WHERE Salary >
    (SELECT AVG(Salary) FROM Employees);

Insight:
Employees earning above average.

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9. Window Function — Running Totals & Rankings

Why it matters:
Powerful analytics without collapsing rows.

Query:

SELECT OrderDate,
       SUM(SalesAmount) OVER (ORDER BY OrderDate) AS RunningSales
FROM Sales;

Use case:
Cumulative sales trend.

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10. DISTINCT — Eliminating Duplicates

Why it matters:
Clean results = correct insights.

Query:

SELECT DISTINCT CustomerID
FROM Orders;

Business question:
How many unique customers placed orders?

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What Interviewers Really Look For

They don’t want:
 ❌ Memorized syntax

They want:
 ✅ Why you used the query
 ✅ What business question it answers
 ✅ How it performs on large data

If you can:

• Explain GROUP BY vs HAVING
• Use JOINs correctly
• Apply CASE and window functions

You are already ahead of most candidates.

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