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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]
Data valuation is a discipline in the fields of accounting and information economics. [1] It is concerned with methods to calculate the value of data collected, stored, analyzed and traded by organizations. This valuation depends on the type, reliability and field of data.
Financial statement analysis (or just financial analysis) is the process of reviewing and analyzing a company's financial statements to make better economic decisions to earn income in future. These statements include the income statement , balance sheet , statement of cash flows , notes to accounts and a statement of changes in equity (if ...
A ratio's values may be distorted as account balances change from the beginning to the end of an accounting period. Use average values for such accounts whenever possible. Financial ratios are no more objective than the accounting methods employed. Changes in accounting policies or choices can yield drastically different ratio values. [6]
That simply defines the extension of the Authentication and Authorization (AA) concept to a more advanced AA and Accounting (AAA) concept. Respective approaches for AAA get defined and staffed in the context of mobile services, when using smart phones as e.a. intelligent agents or smart agents for automated capture of accounting data .
Data analysis uses specialized algorithms and statistical calculations that are less often observed in a typical general business environment. For data analysis, software suites like SPSS or SAS, or their free counterparts such as DAP, gretl, or PSPP are often used. These tools are usually helpful for processing various huge data sets, as they ...
The data from a study can also be analyzed to consider secondary hypotheses inspired by the initial results, or to suggest new studies. A secondary analysis of the data from a planned study uses tools from data analysis, and the process of doing this is mathematical statistics. Data analysis is divided into:
Business mathematics comprises mathematics credits taken at an undergraduate level by business students.The course [3] is often organized around the various business sub-disciplines, including the above applications, and usually includes a separate module on interest calculations; the mathematics itself comprises mainly algebraic techniques. [1]