it is data that has to do with a qualities of something, i.e color shape feel...(etc) while quantitative has to do with numbers and quantities.
In computer science, the concept of data distribution stands for qualative variables. Data is typically the result of some form of measurement that is visualized using graphs or images.
data what kind of dataquantitative data.
The information collected from an observation is called data.
DATA
it means the data is different; the data varies.
Quantitative data deals with numbers and data that are measurable. Qualitative data, meanwhile, deals with descriptions and data that are observable but not measurable.
In computer science, the concept of data distribution stands for qualative variables. Data is typically the result of some form of measurement that is visualized using graphs or images.
Qualative
Qualitative observations could also be called qualitative data, and would be data not related to exact numbers. Such observations could be warmth, flavor, gender, or yes-no answers to questions.
qualative and quantitative
The 'qualative' appeal
Qualative
qualative skills include analytical tools such as statistics, forecasting, risk management, and LEAN Six Sigma
Non-participant observation is primarily considered a qualitative research method. It involves the researcher observing subjects in their natural environment without intervening or influencing their behavior, allowing for the collection of rich, descriptive data. This approach focuses on understanding the context and meanings of social interactions rather than quantifying behaviors. However, observations can sometimes be quantified if specific behaviors are systematically recorded.
Metadata is data that is about data.?æ Although it describes the data, it's not considered business data. Master data is business data. Run-time data is data that is in the process of being run.
Data Store Data Reserve Data Stow Data Warehouse Data Repository Data Depot Data Storehouse
A data dictionary is a repository that contains definitions of data processes, data flows, data stores, and data elements used in an organization. It helps to provide a common understanding of data terminologies and structures within a dataset or system. Data dictionaries are often used to maintain consistency and clarity in data management and analysis processes.