Cambridge Syllabus Notes

Topic: 1 Data processing and information

Objective: Identify direct and indirect data sources

📚 In this lesson we’ll learn how to spot the places where data comes from. Think of data like ingredients in a recipe: some are added straight from the kitchen (direct), while others are made from other ingredients (indirect). By the end, you’ll be able to list both types and give examples for each.

Direct Data Sources

🔍 Surveys and Questionnaires – questions answered by people.
💾 Transaction Records – sales, purchases, or bookings logged by a system.
📡 Sensor Readings – temperature, GPS, or heart‑rate data captured by devices.
🗂️ Manual Entry – data typed directly into a database by a user.
📺 Video/Audio Capture – recordings that are later transcribed or analyzed.

Indirect Data Sources

📊 Aggregated Statistics – averages or totals derived from many direct records.
🧩 Derived Variables – new values calculated from existing data (e.g., BMI = weight/(height²)).
🔗 Linked Data – information obtained by joining tables or databases.
🧠 Inferred Data – predictions or classifications made by algorithms.
📚 Secondary Sources – data published in reports or research papers that was originally collected elsewhere.

Comparison Table

Source Type	Example	Why It’s Direct/Indirect
Direct	Customer purchase log	Recorded at the point of sale, no processing needed.
Indirect	Average monthly sales per region	Calculated from many purchase logs.
Direct	Temperature reading from a weather station	Captured directly by the sensor.
Indirect	Estimated rainfall using satellite imagery	Derived from satellite data, not measured directly.

Quick Activity

Think of a device you use daily (e.g., a smartwatch). List at least two direct data sources it uses.
Identify one indirect data source that could be created from the smartwatch data.
Write a short sentence explaining why the second source is indirect.

💡 Remember: Direct data is the raw, unprocessed information you get straight from the source. Indirect data is built on top of direct data, often through calculations, aggregation, or inference. Spotting the difference helps you choose the right data for your analysis and ensures you understand its reliability and limitations.

Identify direct and indirect data sources