Collecting and organising data

The essentials

Data is a collection of raw facts and figures, such as numbers, words, measurements or observations. After it is processed, it becomes information that helps in decision-making. Businesses use data on sales to plan stock, hospitals use patient records, and governments use census data to plan schemes.

Key points

• Structured data: organised in a fixed format such as rows and columns of a table or spreadsheet; easy to search and process. Example: a marks register.
• Unstructured data: has no fixed format, such as emails, social media posts, images, audio and video.
• Semi-structured data: has some organisation through tags, such as data in HTML or JSON files.
• Primary data: collected first-hand for a specific purpose through surveys, interviews, observation or experiments.
• Secondary data: already collected by someone else, such as published reports, government records or websites.
• Data storage: data is stored in files or databases on devices such as hard disk drives (HDD), solid state drives (SSD), pen drives and memory cards, or on cloud storage accessed over the Internet.
• Data processing cycle: collect → organise and store → process (sort, calculate, summarise) → present as information.
• Data should be accurate, complete and up to date; wrong data leads to wrong decisions ("garbage in, garbage out").
• Big data refers to extremely large and varied data sets that ordinary tools cannot handle easily.

Exam tips

• Situation questions ask you to classify data: a student's own questionnaire gives primary data; figures copied from a government report are secondary data.
• Data vs information: raw marks are data; a class average or ranking is information.

Common mistakes

• Calling an image "structured" because it is stored as a file. Its content has no row–column format.
• Assuming secondary data is always less reliable; it depends on the source.