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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]
Tukey defined data analysis in 1961 as: "Procedures for analyzing data, techniques for interpreting the results of such procedures, ways of planning the gathering of data to make its analysis easier, more precise or more accurate, and all the machinery and results of (mathematical) statistics which apply to analyzing data." [3]
Data analysis focuses on the process of examining past data through business understanding, data understanding, data preparation, modeling and evaluation, and deployment. [8] It is a subset of data analytics, which takes multiple data analysis processes to focus on why an event happened and what may happen in the future based on the previous data.
Toad Data Modeler: Quest Software: SMBs and enterprises Proprietary: Access, IBM Db2, Informix, MySQL, MariaDB, PostgreSQL, MS SQL Server, SQLite, Oracle: Windows Standalone 2005 (before this date known as CaseStudio) Tool Creator Target Business Size License Supported Database Platforms Supported OSs Standalone or bundled into a larger toolkit ...
Mascot performs mass spectrometry data analysis through a statistical evaluation of matches between observed and projected peptide fragments. [6] MassMatrix: Freeware: MassMatrix is a database search algorithm for tandem mass spectrometric data. It uses a mass accuracy-sensitive, probabilistic scoring model to rank peptide and protein matches ...
Data analysis is a systematic method of cleaning, transforming and modelling statistical or logical techniques to describe and evaluate data. [44] Using data analysis as an analytical skill means being able to examine large volumes of data and then identifying trends within the data.