DAPS - Data-Analytic Problem Structure

A practical flowdown diagram to aid the definition of data science projects

Models for structuring big-data and data-analytics projects typically start with a definition of the project’s goals and the business value they are expected to create. The literature identifies proper project definition as crucial for a project’s success, and also recognizes that the translation of business objectives into data-analytic problems is a difficult task. Unfortunately, common project structures, such as CRISP-DM, provide little guidance for this crucial stage when compared to subsequent project stages such as data preparation and modeling. This paper contributes structure to the project-definition stage of data-analytic projects by proposing the Data-Analytic Problem Structure (DAPS). The diagrammatic technique facilitates the collaborative development of a consistent and precise definition of a data-analytic problem, and the articulation of how it contributes to the organization’s goals. In addition, the technique helps to identify important assumptions, and to break down large ambitions in manageable subprojects.I co-authored a peer-reviewed paper that compares the different modeling approaches for analytical problem solving.