Model-driven data analytics (MDDA): Resources for teachers and students

The technique of model-driven data analytics (MDDA) involves the creation of a path model expressing an applied theory, and testing the model using path analysis with latent variables. The latter, path analysis with latent variables, is generally known as structural equation modeling (SEM).

MDDA emerged from the work of a special category of users of the software WarpPLS – data analysis consultants, who regularly work with organizations to provide data-driven recommendations.

While MDDA can be implemented through a variety of software tools, it has found wide adoption among WarpPLS users, because of the many powerful features of this software that can be used in this context. Moreover, in WarpPLS all analyses are model-driven, which makes this software much more user-friendly than other software tools that rely on extensive scripting to conduct analyses.

The website linked below provides several resources for teachers and students, including: a textbook, which may be used by teachers of university courses on MDDA, as a free online document; datasets, which include not only data; but also scenarios, questions, and variables (these are used to illustrate how MDDA can be used to address the needs of various organizations), and YouTube videos, which provide step-by-step illustrations of how to analyze data in the context of scenarios, questions, and variables.

https://scriptwarp.com/mdda