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Background: System Development Life Cycles (SDLC) are proposed through development methodologies (e.g. Rational Unified Process) and international standards (e.g. ISO/IEC 12207) to guide the systematic development of software products to meet expected time, budget, and functional quality. The ISO/IEC 29110-5-1-2: Software engineering guidelines for the generic Basic profile standard provides a disciplined-systematic lightweight SDLC alternative to agile approaches for businesses interested in ISO/IEC certifications rather than agile ones. However, its utilization in the domain of Big Data Analytics Systems has not been investigated.Objective: Big Data Analytics Systems (BDAS) have been proposed using rigorous SDLCs such as CRISP-DM, Team Data Science Process, and Domino Data Science Lifecycle, but their utilization for small business - or small teams called Very Small Entities (VSEs) - is scarcely reported given the requirements demanding human, technological and financial resources not available in small business. Given this problematic situation, new agile SDLCs for BDAS have been proposed such as Data-Driven Scrum, but some small organizations still require the utilization of a more systematic development process, and thus SDLCs based on ISO/IEC standards are expected.Methods: In this research, the design of Light Data Science - Analytics Methodology (LDSAM) and its pilot usability evaluation from a sample of 27 international practitioners are reported. LDSAM is a lightweight development methodology aligned to the ISO/IEC 29110 - Basic Profile - created especially for VSEs.Results: LDSAM was elaborated using Design Science Research Methodology. Initial usability evaluation results of LDSAM are satisfactory, but further empirical research is encouraged to advance to more mature and stable lightweight SDLCs for BDAS.Conclusion: The LDSAM was successfully developed, and its usability was evaluated by a pilot sample of international academics and professionals. Favorable results were obtained on the usability metrics for the proposed LDSAM SDLC for BDAS.
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Montoya-Murillo et al. (2026) studied this question.
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