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1. Data collection 1. Select the right data type 2. Determine the time frame for data collection 3. How
considerations the data will be collected 4. How much data to collect 5. Choose data sources 6.
Decide what data to use
2. Population All possible data values in a certain dataset
3. Sample A part of the population that is representative of the population
4. First-party data Data collected by an individual or group using their own resources
5. Second-party Data collected by a group directly from its audience and then sold
data
6. Third-party data Data collected from outside sources who did not collect it directly
7. Internal data (Pri- Collected by a researcher from first-hand sources
mary data)
8. External data Gathered by other people or from other research
(Secondary data)
9. Quantitative data Can be measured and counted using numbers (quantity, amount, range)
10. Qualitative data Cannot be counted, measured or easily expressed in numbers (names, cate-
gories, descriptions)
11. Discrete data Data that is counted and has a limited number of values
12. Continuous data Data that is measured and can have any numeric value
13. Nominal data A type of qualitative data that is categorized without a set order
14. Ordinal data A type of qualitative data with a set order or scale
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15. Structured data Data organized in a certain format such as rows and columns
16. Unstructured Data that is not organized in an easily identifiable manner
data
17. Data model A model that is used for organizing data elements and how they relate to one
another
18. Data elements Pieces of information, such as people's names, account numbers, and addresses
19. Data modeling The process of creating diagrams that visually represent how data is organized
and structured
20. Levels of data 1. Conceptual modeling 2. Logical data modeling 3. Physical data modeling
modeling
21. Physical data Defines all entities and attributes used.
model
22. Entity Relation- Visual way to understand the relationship between entities in the data model.
ship Diagram
(ERD)
23. Unified Modeling Detailed diagrams that describe the structure of a system by showing the system's
Language (UML) entities, attributes, operations, and their relationships.
24. Data type A specific kind of data attribute that tells what kind of value that is.
25. Text or string A sequence of characters and punctuation that contains textual information.
26. Boolean Data type with only two possible values: true or false.
27. Operator A symbol that names the operation or calculation to be performed.