Business-driven data analytics: A conceptual modeling framework

The effective development of advanced data analytics solutions requires tackling challenges such as eliciting analytical requirements, designing the machine learning solution, and ensuring the alignment between analytics initiatives and business strategies, among others. The use of conceptual modeling methods and techniques is seen to be of considerable value in overcoming such challenges. This paper proposes a modeling framework (including a set of metamodels and a set of design catalogues) for requirements analysis and design of data analytics systems. It consists of three complementary modeling views: business view, analytics design view, and data preparation view. These views are linked together to connect enterprise strategies to analytics algorithms and to data preparation activities. The framework includes a set of design catalogues that codify and represent an organized body of business analytics design knowledge. As the first attempt to validate the framework, three real-world data analytics case studies are used to illustrate the expressiveness and usability of the framework. Findings suggest that the framework provides an adequate set of concepts to support the design and implementation of analytics solutions.