A Proposal for an Interactive Assistant to Support Exploratory Data Analysis in Educational Settings

In the realm of data science, the critical phases of data pre-processing and exploratory data analysis (EDA) play a fundamental role in ensuring the quality of data for downstream processes. However, these phases often present formidable challenges, characterized by complexity and a plethora of available techniques and tools, which can be overwhelming, especially for users with varying levels of expertise. In response to this challenge, we propose the development of EDAQuest, an interactive assistant designed to guide students and novice professionals through the intricate landscape of data pre-processing and exploratory analysis. EDAQuest’s primary objective is to offer a didactic approach that not only enhances users’ comprehension but also enables practical application across diverse datasets. Users can anticipate real-time recommendations, invaluable tips, and informative visual aids to enrich their data understanding. Recognizing the diverse nature of data, EDAQuest aims at proficiently handle heterogeneous data sources by customizing pre-processing techniques for each data type, ensuring optimal outcomes and results. This paper provides an overview of the workflow designed to support EDAQuest’s developmental prototype.