AI - Types of Data

1. Structured Data • Everything is organized into fixed fields (like a spreadsheet). • Easy for computers to read and search. • Stored usually in relational databases (SQL). Examples: • Bank transactions (Date, Amount, Payee) • Student grades (Name, Subject, Score) ⸻ 2. Unstructured Data • No fixed format or organization. • Hard for machines to search directly — needs special tools (like NLP or Computer Vision). • Makes up ~80% of all data in the world! Examples: • A video recording (no obvious fields) • A random tweet or Instagram post • An image from a security camera ⸻ 3. Semi-Structured Data • Partly organized — has some tags, keys, or structure, but not as rigid as a table. • Flexible format — easier to manage than unstructured data, but not fully structured. Examples: • JSON from an API, XML documents Structured, Unstructured, and Semi-structured Data Discrete v/s Continuous Data Measurement Scales for Data

Apr 27, 2025 - 08:04

1. Structured Data

   •  Everything is organized into fixed fields (like a spreadsheet).
• Easy for computers to read and search.
• Stored usually in relational databases (SQL).

Examples:
• Bank transactions (Date, Amount, Payee)
• Student grades (Name, Subject, Score)

⸻

2. Unstructured Data

• No fixed format or organization.
• Hard for machines to search directly — needs special tools (like NLP or Computer Vision).
• Makes up ~80% of all data in the world!

Examples:
• A video recording (no obvious fields)
• A random tweet or Instagram post
• An image from a security camera

⸻

3. Semi-Structured Data

• Partly organized — has some tags, keys, or structure, but not as rigid as a table.
• Flexible format — easier to manage than unstructured data, but not fully structured.

Examples:
• JSON from an API, XML documents

Structured, Unstructured, and Semi-structured Data

Discrete v/s Continuous Data

Measurement Scales for Data