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Data profiling utilizes methods of descriptive statistics such as minimum, maximum, mean, mode, percentile, standard deviation, frequency, variation, aggregates such as count and sum, and additional metadata information obtained during data profiling such as data type, length, discrete values, uniqueness, occurrence of null values, typical string patterns, and abstract type recognition.
Here is a hypothetical example of what a university overview topic might look like, as well as three hypothetical subtopics. As with the example above, trying to create a topic with every article related to a university would be almost impossible, but virtually all other articles about the university would fall within the scope of at least one of the non-lead articles in the overview topic.
Profiles must also be classified according to the kind of subject they refer to. This subject can either be an individual or a group of people. When a profile is constructed with the data of a single person, this is called individual profiling (Jaquet-Chiffelle 2008). This kind of profiling is used to discover the particular characteristics of ...
A demographic profile is a form of demographic analysis in which information is gathered about a group to better understand the group's composition or behaviors for the purpose of providing more relevant services. In business, a demographic profile is usually used to increase marketing efficiency.
In the information sciences, an application profile consists of a set of metadata elements, policies, and guidelines defined for a particular application. [1]The elements may come from one or more element sets, thus allowing a given application to meet its functional requirements by using metadata from several element sets - including locally defined sets.
For example see: Binary option) While an attribute is often intuitive, the variable is the operationalized way in which the attribute is represented for further data processing . In data processing data are often represented by a combination of items (objects organized in rows), and multiple variables (organized in columns).
The data management plan describes the activities to be conducted in the course of processing data. Key topics to cover include the SOPs to be followed, the clinical data management system (CDMS) to be used, description of data sources, data handling processes, data transfer formats and process, and quality control procedure
A research statement is a summary of research achievements and a proposal for upcoming research. It often includes both current aims and findings, and future goals. Research statements are usually requested as part of a relevant job application process, and often assist in the identification of appropriate applicants. [1]