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.

History

In 1988, an Italian-Dutch-French-English consortium that organized an international meeting on the multiway data analysis in Rome. In recent year, the development and application of multiway data analysis has extended to food industry and become an useful tool for chemometricians.

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 orders of multiway data starting from line chart ending with multinational corporation deployed their multiway data over cloud infrastructure:

• One-way data looks like a line chart displays information as a series of data points connected by straight line segments.
• 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 from existing heterogeneous IT infrastructure over so called 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 generate concise information for management team (e.g. a line chart showing trend analysis of monthly consolidated productivity index) 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:

• Computer vision
• Electroanalytical chemistry
• Neuroscience
• Process analysis
• Social network analysis/web-mining

Following multiway applications is not new to the field of studies and works:

• Auditing and assurance
• Financial and management accounting

However participants of these two fields seldom address their research studies and professional publication attributed to the terminology "multiway data analysis". Following are some of relevant terminologies associated with multiway data analysis:

Classified by IT terminologies:

• Aggregation and consolidation
• Tagging and denormalization
• System integration
• Data mapping

Classified by marketing terminologies:

• Business Intelligence (BI)
• Business Process Management (BPM)
• Enterprise Performance Management (EPM)
• Extract, transform, load (ETL)
• Record to report (R2R)

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.

See also

• AVESTA computing issues of financial and management accounting
• List of data structures
• Mathematics
• Multilinear subspace learning