Business Analytics Types

Interactive lecture demonstration — Philippine sari-sari store

Descriptive → Diagnostic → Predictive → Prescriptive

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Use Your Own CSV Dataset

Choose a CSV file and click Load CSV. The application works entirely in your browser.

Built-in synthetic Philippine dataset is loaded.

Recommended columns: date, product, category, sales_php, branch. The app also recognizes common alternatives such as sales, revenue, amount, total, item, store, and location.

1. Descriptive Analytics — What happened?

Descriptive analytics summarizes historical data using totals, averages, counts, rankings, tables, and charts.

Question: How much did the stores sell, and which products generated the most sales?

Sales by Product

2. Diagnostic Analytics — Why did it happen?

Diagnostic analytics examines differences and patterns to investigate possible explanations for an observed result.

Question: Why are sales different across branches and categories?

Branch: Sales: —Transactions: —Average: —

Sales by Category

Reminder: A difference or pattern does not automatically prove causation.

3. Predictive Analytics — What might happen?

Predictive analytics uses historical patterns or models to estimate likely future outcomes.

This demonstration uses a simple 14-day moving-average baseline.

4. Prescriptive Analytics — What should we do?

Prescriptive analytics uses evidence, predictions, rules, or optimization to recommend actions.

Simple Restocking Recommendation

Real business decisions: also consider inventory, profit margin, supplier lead time, expiry, cash, seasonality, and business goals.

Distinguishing the Four Types

Type	Main Question	Example
Descriptive	What happened?	Total sales last month
Diagnostic	Why did it happen?	Why one branch sold less
Predictive	What might happen?	Expected sales next week
Prescriptive	What should we do?	Which products to prioritize for restocking

What happened? → Why? → What might happen? → What should we do?