Learning Unit 1
Differentiate Between Data and Information
Data: Raw facts and figures without meaning.
Example: 23, Johannesburg, 85%
Information: Processed data that has meaning and is useful for decision-making.
Example: “23 students from Johannesburg passed with an 85% average.”
Key difference: Data is raw input, Information is meaningful output
Differentiate Between Structured and Unstructured Data
Structured Data: Organized and stored in tables or spreadsheets. Easy to search and
analyse.
Example: Excel spreadsheets, databases.
Unstructured Data: No specific format or structure. Difficult to organize/analyse without
special tools.
Example: Emails, videos, social media posts, images.
Requires advanced tools to analyse (AI, machine learning)
Feature Structured Data Unstructured Data
Format Organized (table) Unorganized (media)
Storage Databases File systems, cloud storage
Examples Sales database WhatsApp voice note
Differentiate Between Quantitative and Qualitative Data
Quantitative Data: Numerical data that can be measured and calculated
Example: sales totals, average goals
Qualitative Data: Descriptive data that expresses qualities or characteristics, not mathematic
Example: customer feedback
Ratings (1–5 stars) = quantitative, free-text reviews = qualitative
If it can be counted, it's quantitative. If it describes, it’s qualitative
Explain the Purpose of Data in Business
Regulatory compliance: accurate records required by law (e.g., tax, finance)
Decision-making: measure, control, improve business processes
Key uses:
Find new customers
Retain customers
Improve products/services
Predict sales trends
Identify the Sources of Data in Business
Internal = generated inside the business (e.g., sales, payroll, stock, company reports)
External = generated outside the business (e.g., market research, competitor analysis, social
media)
Differentiate Between Data and Information
Data: Raw facts and figures without meaning.
Example: 23, Johannesburg, 85%
Information: Processed data that has meaning and is useful for decision-making.
Example: “23 students from Johannesburg passed with an 85% average.”
Key difference: Data is raw input, Information is meaningful output
Differentiate Between Structured and Unstructured Data
Structured Data: Organized and stored in tables or spreadsheets. Easy to search and
analyse.
Example: Excel spreadsheets, databases.
Unstructured Data: No specific format or structure. Difficult to organize/analyse without
special tools.
Example: Emails, videos, social media posts, images.
Requires advanced tools to analyse (AI, machine learning)
Feature Structured Data Unstructured Data
Format Organized (table) Unorganized (media)
Storage Databases File systems, cloud storage
Examples Sales database WhatsApp voice note
Differentiate Between Quantitative and Qualitative Data
Quantitative Data: Numerical data that can be measured and calculated
Example: sales totals, average goals
Qualitative Data: Descriptive data that expresses qualities or characteristics, not mathematic
Example: customer feedback
Ratings (1–5 stars) = quantitative, free-text reviews = qualitative
If it can be counted, it's quantitative. If it describes, it’s qualitative
Explain the Purpose of Data in Business
Regulatory compliance: accurate records required by law (e.g., tax, finance)
Decision-making: measure, control, improve business processes
Key uses:
Find new customers
Retain customers
Improve products/services
Predict sales trends
Identify the Sources of Data in Business
Internal = generated inside the business (e.g., sales, payroll, stock, company reports)
External = generated outside the business (e.g., market research, competitor analysis, social
media)
