📌 Oracle SQL — Aggregate Functions, GROUP BY & HAVING 🚀

Aggregate functions turn raw data into real insights — totals, averages, counts, highs, lows. Add GROUP BY and HAVING, and you’ve unlocked 90% of reporting + analytics use cases in SQL.
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🎥 Concept

🔽 MIN → lowest value
🔼 MAX → highest value
➕ SUM → total
🧮 AVG → average
🔢 COUNT → row count
❌ NULLs ignored
🔀 GROUP BY → split data
🚫 HAVING → filter groups
🎯 WHERE → filter rows
⚙️ Execution Order → FROM → WHERE → GROUP → HAVING → ORDER
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📖 Definitions

🔽 MIN / 🔼 MAX

Return lowest / highest values.

➕ SUM

Adds all numeric values.

🧮 AVG

Computes average (NULLs skipped).

🔢 COUNT

Counts rows or non-null values.

🔀 GROUP BY

Splits data into subsets; aggregates run per group.

🚫 HAVING

Filters groups using aggregate conditions.

⚙️ Execution Order

1️⃣ FROM → pick tables
2️⃣ WHERE → filter rows
3️⃣ GROUP BY → create groups
4️⃣ HAVING → filter groups
5️⃣ ORDER BY → sort output
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🧠 Analogy

Aggregates = class report card:
MIN = lowest marks
MAX = topper’s score
AVG = class average
SUM = total marks
COUNT = number of students
GROUP BY = each class section
HAVING = only show sections meeting conditions
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🔍 Examples

Highest salary → MAX(salary)
Employee count → COUNT(*)
City-wise customers → GROUP BY city
Departments with total salary - 50k → HAVING SUM(salary)-50000
Top-performing cities → HAVING COUNT(*) to-5
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📊 Fact

Every enterprise dashboard — HR, finance, CRM, inventory, analytics — uses GROUP BY + aggregates behind the scenes.
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Master Aggregate Functions + GROUP BY + HAVING → and every reporting, analytics, or QA validation query becomes effortless.
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💡 Tips & Tricks

🔥 Non-aggregate columns must be in GROUP BY
🔥 WHERE filters rows before grouping
🔥 HAVING filters groups after grouping
🔥 Never use SUM for row-level totals — use NVL(col1,0)+NVL(col2,0)
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🔑 Shortcut to Remember

Aggregates = Many rows → One result
GROUP BY = Split → Summarize
HAVING = Filter summary
FWGHO = From → Where → Group → Having → Order
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