![](https://blog.win-source.net/wp-content/uploads/2020/04/120.png)
* Question
What types of data can be classified based on the source of the data generation?
* Answer
Data can be classified based on the source of its generation into several key types, each with distinct characteristics and uses. Here are the primary categories:
1. Primary Data:
– Definition: Data collected directly from the source by the researcher for the first time.
– Examples: Surveys, interviews, experiments, direct observations.
2. Secondary Data:
– Definition: Data that has already been collected and processed by others.
– Examples: Books, articles, reports, previously conducted surveys, databases.
3. Tertiary Data:
– Definition: Data that comes from the synthesis or compilation of primary and secondary sources.
– Examples: Encyclopedias, dictionaries, bibliographies, directories.
4. Quantitative Data:
– Definition: Data that can be quantified and verified, and is amenable to statistical manipulation.
– Examples: Temperature readings, sales figures, population counts.
5. Qualitative Data:
– Definition: Non-numerical data that is used to understand concepts, thoughts, or experiences.
– Examples: Interviews, observations, anecdotes.
6. Big Data:
– Definition: Extremely large datasets that may be complex, unstructured, and difficult to manage with traditional tools.
– Examples: Social media data, Internet of Things (IoT) data, real-time surveillance data.
7. Administrative Data:
– Definition: Data collected for administrative (rather than research) purposes.
– Examples: School records, hospital records, financial records.
8. Machine-Generated Data:
– Definition: Data generated automatically by devices or processes without human intervention.
– Examples: Sensors data, log files, satellite images.
9. Human-Generated Data:
– Definition: Data that is generated by humans, either through direct entry or interactions.
– Examples: Social media posts, user-generated reviews, manual data entry records.
These categories help in understanding the origin and nature of the data, guiding how it can be used, processed, and analyzed effectively.
COMMENTS