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Multimethodology or multimethod research includes the use of more than one method of data collection or research in a research study or set of related studies.Mixed methods research is more specific in that it includes the mixing of qualitative and quantitative data, methods, methodologies, and/or paradigms in a research study or set of related studies.
Data integration refers to the process of combining, sharing, or synchronizing data from multiple sources to provide users with a unified view. [1] There are a wide range of possible applications for data integration, from commercial (such as when a business merges multiple databases) to scientific (combining research data from different bioinformatics repositories).
Secondary data refers to data that is collected by someone other than the primary user. [1] Common sources of secondary data for social science include censuses, information collected by government departments, organizational records and data that was originally collected for other research purposes. [2]
Secondary research is contrasted with primary research in that primary research involves the generation of data, whereas secondary research uses primary research sources as a source of data for analysis. [1] A notable marker of primary research is the inclusion of a "methods" section, where the authors describe how the data was generated.
In the social sciences, triangulation refers to the application and combination of several research methods in the study of the same phenomenon. [1] By combining multiple observers, theories, methods, and empirical materials, researchers hope to overcome the weakness or intrinsic biases and the problems that come from single method, single-observer, and single-theory studies.
Data is collected from a variety of sources. [16] [17] A list of data sources are available for study & research. The requirements may be communicated by analysts to custodians of the data; such as, Information Technology personnel within an organization. [18]
Data blending is a process whereby big data from multiple sources [1] are merged into a single data warehouse or data set. [ 2 ] Data blending allows business analysts to cope with the expansion of data that they need to make critical business decisions based on good quality business intelligence . [ 3 ]
Data science is multifaceted and can be described as a science, a research paradigm, a research method, a discipline, a workflow, and a profession. [ 4 ] Data science is "a concept to unify statistics , data analysis , informatics , and their related methods " to "understand and analyze actual phenomena " with data . [ 5 ]