Abstract

CHAMOLI FALCON, Andy Williams; CABRERA SANTA CRUZ, Maria Julia; LOBATON GUTIERREZ, Carlos Augusto  and  PATINO GARCIA, Guiceli Codina. PYTHON LIBRARIES AS INTEGRATION ENGINES IN BI: A SYSTEMATIC REVIEW OF THEIR CONTRIBUTION TO BUSINESS OPERATIONAL EFFICIENCY. Aula Virtual [online]. 2025, vol.6, n.13, e622.  Epub Jan 23, 2026. ISSN 2665-0398.  https://doi.org/10.5281/zenodo.18280978.

The increasing complexity of business intelligence systems and the diversity of data sources in organizations have heightened the need for solutions capable of efficient integration, making interoperability a strategic component for optimizing operational processes. In this context, this article aims to evaluate the impact of interoperability on the operational efficiency of companies using Python libraries for business intelligence, in order to understand how these tools contribute to improving organizational performance. To this end, a systematic review article was developed based on a structured methodological process that included inclusion and exclusion criteria, as well as a comparative analysis of studies published in the last five years, aligned with the PRISMA guidelines. The results show that Python libraries facilitate data integration, automate analytical workflows, and reduce processing times, generating direct improvements in the availability, quality, and timeliness of the information used for decision-making. Furthermore, a consistent trend toward the use of Python as an intermediary layer between heterogeneous systems is observed. In conclusion, the interoperability enabled by these libraries is a key factor in increasing operational efficiency in BI-based enterprise environments, establishing itself as an essential tool for strengthening organizational competitiveness.

Keywords : Interoperability; operational efficiency; Python libraries; business intelligence; data integration.

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