Data vs. Information
Basic Building Blocks of Information & Their Characteristics
1. Data vs. Information
Data represents raw, unorganized facts and figures fed into a system[cite: 1]. Data consists of numbers, characters, symbols, sounds, or images that lack inherent meaning and are not organized to make decisions[cite: 1].
- Quantitative Data: Numerical data collected through measurement or direct counting (e.g., student examination scores)[cite: 1]. Can be ordered and computed mathematically[cite: 1].
- Qualitative Data: Non-measurable descriptive observations representing distinct properties or attributes (e.g., goodwill of an enterprise)[cite: 1].
- Information: Data processed, structured, and organized into a meaningful context to assist decision-making[cite: 1].
- Relational Dependency: Information output by one processing system can serve as raw input data for another system[cite: 1].
2. The Life Cycle of Data
Input / Capture
Store / Maintain
Purge / Destroy
- Data Creation: Introducing or generating data inside the system for processing[cite: 1].
- Data Management: Securing data, maintaining validity, and ensuring ongoing availability[cite: 1].
- Removal of Obsolete Data: Safely purging outdated or unneeded records[cite: 1].
3. Characteristics of Valuable Information
| Attribute | Description |
|---|---|
| Timeliness[cite: 1] | Must be up to date and available when decisions are taken; value decreases as time passes[cite: 1]. |
| Accuracy[cite: 1] | Information must be accurate and free of errors to enable correct conclusions[cite: 1]. |
| Completeness[cite: 1] | Must include sufficient context; partial details prevent informed decisions[cite: 1]. |
| Relevance[cite: 1] | Value depends on how directly it fits the operational requirements of the user[cite: 1]. |
| Understandability[cite: 1] | Must be structured clearly and unambiguously so the recipient can interpret it without confusion[cite: 1]. |
Traditional RDBMS platforms are supplemented by modern Big Data systems evaluated on six dimensions: Volume (terabytes to petabytes of data)[cite: 1], Velocity (high-speed real-time data ingestion)[cite: 1], Variety (structured, semi-structured, and unstructured data), Veracity (data trustworthiness and accuracy), Value (actionable insights extracted for business operations)[cite: 1], and Variability (data stream flow shifts).
State the Golden Rule of Information and explain why a live stock-market ticker loses value as time elapses[cite: 1].
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