Multiway data analysis
Multiway data analysis is distinguished from multivariate analysis, multilevel analysis and multidimensional analysis. It refers to any multiple array can be analyzed through a design and application of multiple methodologies.[1]
History
In 1988, an Italian-Dutch-French-English consortium that organized an international meeting on the multiway data analysis in Rome.[2] In recent year, the development and application of multiway data analysis has extended to food industry and become an useful tool for chemometricians. [3]
Composition of Multiway Data Analysis
Multiway Data
Some of research papers in this field of study apply mathematical notation to describe multiway data. Following provide a simplex example to describe different levels of multiway data starting from bar chart ending with cloud infrastructure:
- One-way data looks like a bar chart displays categorical data in the form of frequency counts.
- Two-way data looks like a spreadsheet it contains row and column spaces.
- Three-way data looks like a set of spreadsheets such as Excel Workbook such that it contains multiple sheets with every sheet contains row and column spaces.
- Fourth-way data looks like a file folder contains multiple Excel Workbooks.
- Fifth-way data looks like a company have invested in IT infrastructure to connect different data storage devices managing multiple file folders together with multiple database and file formats (e.g. Excel, MS SQL, Sybase, DB2, ISAM).
- Sixth-way data looks like a multinational corporation contains multiple subsidiaries operate multiple business across multiple geographical regions their management team have decided to deploy these multiway data over cloud infrastructure.
Multiway Model
Multiway data can be transformed upward or downward to different levels by using suitable model(s). However, transforming the above example of sixth-way data downward to two-way data and to one way data ultimately in order to obtain relevant information for management team will encounter multifaceted problems despite there are multiple methodologies available.
Multiway Application
Multiway data analysis can be employed in various multiway applications so as to address the problem of finding hidden multilinear structure in multiway datasets. Following are examples of applications in different fields: [4]
- Auditing and assurance
- Computer vision
- Electroanalytical chemistry
- Financial and management accounting
- Neuroscience
- Process analysis
- Social network analysis/web-mining
Multiway Processing
Multiway processing is the execution of designed and determined multiway model(s) transforming multiway data to desirable level with addressing the specific need of particular multiway application. A typical example of data generated with a potentiometric electronic tongue illustrate relevant multiway processing.[5]
See also
- AVESTA computing issues of financial and management accounting
- List of data structures
- Mathematics
- Multilinear subspace learning
References
- ^ Coppi, R., S. Bolasco (Eds.): Multiway Data Analysis. North-Holland, Amsterdam 1989, xiv+552 S
- ^ Pieter M. Kroonenberg, Applied Multiway Data Analysis, Wiley 2008, pp. xv.
- ^ http://curis.ku.dk/ws/files/13035961/rasmus_bro.pdf
- ^ http://www.cs.rpi.edu/research/pdf/07-06.pdf
- ^ Raul Cartas, Aitor Mimendia, Andrey Legin, Manel del Valle1,Multiway Processing of Data Generated with a Potentiometric Electronic Tongue in a SIA System, 2011.