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In the business world, descriptive statistics provides a useful summary of many types of data. For example, investors and brokers may use a historical account of return behaviour by performing empirical and analytical analyses on their investments in order to make better investing decisions in the future.
Business analysis is a professional discipline [1] focused on identifying business needs and determining solutions to business problems. [2] Solutions may include a software-systems development component, process improvements, or organizational changes, and may involve extensive analysis, strategic planning and policy development.
Business intelligence (BI) consists of strategies, methodologies, and technologies used by enterprises for data analysis and management of business information. [1] Common functions of BI technologies include reporting, online analytical processing, analytics, dashboard development, data mining, process mining, complex event processing, business performance management, benchmarking, text ...
Overabundance of already collected data became an issue only in the "Big Data" era, and the reasons to use undersampling are mainly practical and related to resource costs. Specifically, while one needs a suitably large sample size to draw valid statistical conclusions, the data must be cleaned before it can be used. Cleansing typically ...
Data collection can be done by observing customer behavior through in-situ studies or by processing e.g. log files, by interviewing customers, potential customers, stakeholders, or a sample of the general population. The data can be quantitative in nature (counting sales, clicks, eye-tracking) or qualitative (surveys, questionnaires, interviews ...
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]