Week 1 Flashcards
What is Data
- Raw Facts
- Represent values of qualitative or quantitative variables
- Often observed and recorded
How is Data collected?
Through observations (subjective)
Through recordings (objective, measured)
Does Data on its own have meaning?
No, unprocessed Data has no meaning
Data must be processed into a useable form that can be understood by the information consumers
How does Data serve in an information system?
It serves as inputs to information
Five Characteristics of Data Quality
- Relevance
- Frequency
- Timeliness
- Accuracy
- Privacy
Data Quality Characteristics: Relevance of Data
What data to collect
Unrelated data are NOT needed, wastage of investment and causes information overload
Data Quality Characteristics: Frequency of Data
How often to collect data?
i.e. weather models
Data Quality Characteristics: Timeliness
When to collect data?
i.e. share price, especially when data is needed in real time
Data Quality Characteristics: Accuracy
Precision of Data?
i.e. speed camera malfunction triggers issuing fines, law suits from citizens
Data Quality Characteristics : Privacy
Protection from unauthorised access/use
Outsourced company employees cannot access financial health related data
Cost of Data
DATA IS NOT FREE
Costs involved in collecting and ensuring data quality through five characteristics
Value generated from data justifies its costs of collection?
Information
Information is the Output of processed data that carries meaning for the information consumers
Allows individuals to make decisions (AI too nowadays)
How is information created?
Through analysing or processing data
How is data processed?
Manually (human intelligence)
IT enabled Information Systems
Relationship between Data, Information & Knowledge
Data -> Information -> Knowledge
Data is processed within a context to give information (understandable meaning)
Knowledge is sought to question meanings of information received from processing data
Knowledge
- Produces insights
- Helps improve understanding relationship between pieces of information
Information Overload (Infobesity)
Too much information will reduce the quality of decision making (too much noise)
Why?
- Overgeneralization
- Selective of information that confirms previous point of view/ experience
3 Issues with Data & Information
- Information Overload
- Information not produced for management decision making
- Decisions driven by power and politics instead of information