joyline yegon
Apr 18
Characteristics of data?
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ChatGPT
Apr 18
1. Accuracy: Data should be free from errors and represent the true values of the information being collected.
2. Relevance: Data should be directly related to the research question or objective at hand.
3. Completeness: Data should be comprehensive and include all relevant information needed for analysis.
4. Consistency: Data should be consistent and not contradict itself or other sources of information.
5. Timeliness: Data should be collected and recorded in a timely manner to ensure its relevance and accuracy.
6. Accessibility: Data should be easily accessible and available for analysis and interpretation.
7. Precision: Data should be precise and provide specific details without ambiguity.
8. Reliability: Data should be reliable and consistent, producing similar results when collected and analyzed multiple times.
9. Validity: Data should be valid and measure what it is intended to measure, without bias or distortion.
10. Repeatability: Data should be repeatable, meaning that the same results can be obtained when the data collection process is repeated under the same conditions.
2. Relevance: Data should be directly related to the research question or objective at hand.
3. Completeness: Data should be comprehensive and include all relevant information needed for analysis.
4. Consistency: Data should be consistent and not contradict itself or other sources of information.
5. Timeliness: Data should be collected and recorded in a timely manner to ensure its relevance and accuracy.
6. Accessibility: Data should be easily accessible and available for analysis and interpretation.
7. Precision: Data should be precise and provide specific details without ambiguity.
8. Reliability: Data should be reliable and consistent, producing similar results when collected and analyzed multiple times.
9. Validity: Data should be valid and measure what it is intended to measure, without bias or distortion.
10. Repeatability: Data should be repeatable, meaning that the same results can be obtained when the data collection process is repeated under the same conditions.
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Google Gemini AI
Apr 18
Characteristics of Data:
1. Volume:
- The amount of data generated, collected, and stored.
2. Velocity:
- The speed at which data is being created and transmitted.
3. Variety:
- The diversity of data types and sources, including structured (e.g., spreadsheets), unstructured (e.g., text, images), and semi-structured (e.g., JSON).
4. Veracity:
- The accuracy, consistency, and completeness of data.
5. Value:
- The potential usefulness and insights that can be derived from the data.
6. Granularity:
- The level of detail or specificity in the data.
7. Accessibility:
- The ease of access and retrieval of data by authorized users.
8. Reliability:
- The consistency and trustworthiness of the data over time.
9. Timeliness:
- The freshness and relevance of the data.
10. Integrity:
- The protection and maintenance of the data's accuracy and completeness.
11. Governance:
- The rules and policies that govern the collection, storage, usage, and disposal of data.
12. Privacy:
- The measures taken to protect sensitive data from unauthorized access or disclosure.
13. Anonymization:
- The process of removing personally identifiable information (PII) from data while preserving its analytical value.
14. Meta-Data:
- Data about data, which provides context and information about the primary data.
15. Interoperability:
- The ability of data to be easily transferred, shared, and combined with other data sources.
1. Volume:
- The amount of data generated, collected, and stored.
2. Velocity:
- The speed at which data is being created and transmitted.
3. Variety:
- The diversity of data types and sources, including structured (e.g., spreadsheets), unstructured (e.g., text, images), and semi-structured (e.g., JSON).
4. Veracity:
- The accuracy, consistency, and completeness of data.
5. Value:
- The potential usefulness and insights that can be derived from the data.
6. Granularity:
- The level of detail or specificity in the data.
7. Accessibility:
- The ease of access and retrieval of data by authorized users.
8. Reliability:
- The consistency and trustworthiness of the data over time.
9. Timeliness:
- The freshness and relevance of the data.
10. Integrity:
- The protection and maintenance of the data's accuracy and completeness.
11. Governance:
- The rules and policies that govern the collection, storage, usage, and disposal of data.
12. Privacy:
- The measures taken to protect sensitive data from unauthorized access or disclosure.
13. Anonymization:
- The process of removing personally identifiable information (PII) from data while preserving its analytical value.
14. Meta-Data:
- Data about data, which provides context and information about the primary data.
15. Interoperability:
- The ability of data to be easily transferred, shared, and combined with other data sources.
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