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Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. [4]
Personal data, also known as personal information or personally identifiable information (PII), [1] [2] [3] is any information related to an identifiable person. The abbreviation PII is widely used in the United States , but the phrase it abbreviates has four common variants based on personal or personally , and identifiable or identifying .
A personality test is a method of assessing human personality constructs.Most personality assessment instruments (despite being loosely referred to as "personality tests") are in fact introspective (i.e., subjective) self-report questionnaire (Q-data, in terms of LOTS data) measures or reports from life records (L-data) such as rating scales.
These researchers first studied relationships between many words related to personality traits. They made lists of these words shorter by 5–10 times and then used factor analysis to group the remaining traits (with data mostly based upon people's estimations, in self-report questionnaires and peer ratings) to find the basic factors of ...
In information science, profiling refers to the process of construction and application of user profiles generated by computerized data analysis.. This is the use of algorithms or other mathematical techniques that allow the discovery of patterns or correlations in large quantities of data, aggregated in databases.
The Data QC process uses the information from the QA process to decide to use the data for analysis or in an application or business process. General example: if a Data QC process finds that the data contains too many errors or inconsistencies, then it prevents that data from being used for its intended process which could cause disruption.
Data exploration is an approach similar to initial data analysis, whereby a data analyst uses visual exploration to understand what is in a dataset and the characteristics of the data, rather than through traditional data management systems. [1]
Data visualization refers to the techniques used to communicate data or information by encoding it as visual objects (e.g., points, lines, or bars) contained in graphics. The goal is to communicate information clearly and efficiently to users. It is one of the steps in data analysis or data science. According to Vitaly Friedman (2008) the "main ...