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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]
It has a tier-based data model that supports multi-level, multi-participant annotation of time-based media. It is applied in humanities and social sciences research (language documentation, sign language and gesture research) for the purpose of documentation and of qualitative and quantitative analysis. [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.
Automated analysis, massive data, and systematic reasoning support decision-making at almost all levels. In general, key technologies employed by software analytics include analytical technologies such as machine learning , data mining , statistics , pattern recognition , information visualization as well as large-scale data computing & processing.
R is a programming language for statistical computing and data visualization. It has been adopted in the fields of data mining, bioinformatics and data analysis. [9] The core R language is augmented by a large number of extension packages, containing reusable code, documentation, and sample data. R software is open-source and free software.
Exploratory data analysis is an analysis technique to analyze and investigate the data set and summarize the main characteristics of the dataset. Main advantage of EDA is providing the data visualization of data after conducting the analysis.
Topological data analysis and persistent homology have had impacts on Morse theory. [121] Morse theory has played a very important role in the theory of TDA, including on computation. Some work in persistent homology has extended results about Morse functions to tame functions or, even to continuous functions [ citation needed ] .
The study of multiway data analysis was first formalized as the result of a conference held in 1988. The result of this conference was the first text specifically addressed to this field, Coppi and Bolasco's Multiway Data Analysis. [1] At that time, the application areas for multiway analysis included statistics, econometrics and psychometrics.
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