GCE A/L ICT - Unit 01 - 2026 Batch
Basics of Data and Information Technology
Differences Between Data, Information, and Their Characteristics
Data:
Raw, unorganized facts such as numbers, diagrams, or photographs that have no specific meaning.
Information:
When data is processed and organized into a meaningful format, it becomes information.
Key Differences Between Data and Information:
| Data | Information |
|---|---|
| Not systematically organized | Systematically organized as a result of processing |
| Has no meaning | Has meaning |
| Large in volume | Can be used for almost all purposes |
| Not useful | Useful |
Types of Data:
-
Quantitative Data:
Data represented as numbers or measurements. -
Recorded Data:
Data stored in devices such as computers or storage devices. -
Unrecorded Data:
Information generally stored in memory or recalled.
Applications of Information Technology:
-
Helping Students’ Academic Development:
- Enhances knowledge through lessons and community activities.
- Enables sharing of information using the internet.
-
Educational Outputs:
- Supports advancements in fields like veterinary work, medicine, and agriculture.
-
Collecting Data for Research:
- Collecting required data and utilizing it for research purposes.
Benefits and Characteristics of Information:
- Helps make decisions easier.
- Systematizes processes and tasks.
GCE A/L ICT - Unit 01 - 2026 Batch
Characteristics of Unorganized Data
- Incomplete (e.g., square root of 2 ≈ 1.41)
- Inconsistent
- Unreliable
- Difficult to analyze
- Lacks clarity
- Cannot make decisions
- Lacks completeness
The Evolution of Data
- Data is no longer just a collection of raw facts; it has transformed into valuable information that gains significance over time.
- In 2014, global advancements made data increasingly important in fields such as work and innovation.
- The evolution of data happens over time, making it a valuable resource known as "information."
Big Data
Big data refers to:
- Large volumes
- Variety
- Velocity
Key Requirements for Big Data Applications:
- Decision-making for large organizations (e.g., business growth, societal developments).
- Handling vast amounts of services and operations.
Big Data Usage
Organizations, along with various platforms, generate and store data in vast quantities, often measured in terabytes.
For example, social media platforms like Facebook and YouTube generate massive amounts of structured and unstructured data (likes, comments, shares) every second, leading to the need for better data analysis and storage systems.
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