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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]
Statistics is the mathematical science involving the collection, analysis and interpretation of data. A number of specialties have evolved to apply statistical and methods to various disciplines. Certain topics have "statistical" in their name but relate to manipulations of probability distributions rather than to statistical analysis.
Data science is "a concept to unify statistics, data analysis, informatics, and their related methods" to "understand and analyze actual phenomena" with data. [5] It uses techniques and theories drawn from many fields within the context of mathematics , statistics, computer science , information science , and domain knowledge . [ 6 ]
Job analysis (also known as work analysis [1]) is a family of procedures to identify the content of a job in terms of the activities it involves in addition to the attributes or requirements necessary to perform those activities. Job analysis provides information to organizations that helps them determine which employees are best fit for ...
It is important to note, however, that the accuracy and usability of results will depend greatly on the level of data analysis and the quality of assumptions. [ 1 ] Predictive analytics is often defined as predicting at a more detailed level of granularity, i.e., generating predictive scores (probabilities) for each individual organizational ...
A business analyst's job description tends to include "creating detailed business analysis, outlining problems, opportunities and solutions for a business, budgeting and forecasting, planning and monitoring, variance and analysis, pricing, reporting, and defining business requirements and reporting back to stakeholders". [3]