This is the first type of analytics → it answers the question:
👉 “What happened?”

Once your data is cleaned, the first step is to summarize it.

🔹 Common Techniques in Descriptive Analytics

1. Totals (Sum) – e.g., total sales in August = ₹1,500.

2. Averages (Mean) – e.g., average daily sales = ₹300.

3. Maximum / Minimum – e.g., highest sales in a day = ₹500, lowest = ₹100.

4. Count – e.g., number of transactions = 30 days.

5. Percentages / Growth – e.g., Week 1 sales vs Week 2 sales (growth rate).

🔹 Example (from cleaned data)

• Total sales = 1450

• Average sales = 290 per day

• Highest sales = 1000 (on 4th Aug)

• Lowest sales = 0 (on 2nd Aug)

This already tells a story:
👉 On one day sales boomed (1000), on another day there were none (0). That’s important for business.

🔹 Tools you can use

• Excel: SUM, AVERAGE, COUNT, MAX, MIN, Pivot Tables.

• SQL: SUM(), AVG(), COUNT(), MAX(), MIN().

✅ Checkpoint for you:
If you were showing this sales data to a manager, which 2 descriptive analytics points would you highlight first? (Total sales, average, highest, lowest, etc.)