Landscape of Tools for Business Analytics and Data Science – A Tutorial on KNIME

The growing prominence of business analytics and data science in both industry and academia has amplified the demand for impactful educational methodologies. As educational institutions worldwide introduce programs at different academic levels, it is imperative to identify approaches that offer comprehensive knowledge while remaining accessible to less technical student bodies. One established method for enriching the learning experience involves the adoption of a visual, workflow-type, no-code software platform. This strategy aims to hide the syntactic nature of data science, thereby allowing greater focus on fundamental concepts and best practices of analytics projects. This article aims to shed light into the landscape of data science software tools and demonstrate the favorable capabilities of a leading free and open-source low-code modeling environment, named KNIME Analytics Platform, as an ideal tool for intuitive learning, teaching, and practical application in the realms of business analytics, data science, and machine learning including its ability to develop and consume AI models, including Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) models.