A Data Pipeline Concept for Digitizing Services in Small and Medium-Sized Companies - Chikhalkar, Akshay; Brünninghaus, Marc; Deppe, Sahar; Bicker, Eckard; Röcker, Carsten (JOIV : International Journal on Informatics Visualization, 2025)
Small and medium-sized enterprises face significant challenges in their digital transformation due to their limited resources compared to larger companies. In order to overcome these issues, this study proposes the idea of a data pipeline that is affordable and accessible for small and medium-sized enterprises. The suggested method conceptualizes an Extract, Transform and Load (ETL) procedure, which is a go-to approach for data engineering using open-source technologies. A case study of a mobile assistance system is used to illustrate this data flow and emphasizes its numerous advantages and practical uses. Small and medium-sized enterprises can use this data pipeline as a jumping-off point to create a cost-effective, efficient, and scalable data infrastructure. Because the pipeline’s components are modular and completely independent of one another, it is simple to expand, modify, or use individually to meet specific business needs. A basic dashboard prototype that can be modified for different applications is created to show the concept’s viability. Although pipeline design is provided by the concept, its successful execution necessitates technical know-how. To handle resource constraints and data anomalies, this research highlights the necessity of standardized procedures and careful tool selection. The data pipeline’s output may eventually be utilized for sophisticated analytical functions, giving small and medium-sized enterprises the competitive edge they need in the digital era by enabling them with data-driven solutions.