| Summary: | Background. The paper raises the problem of building a software architecture
for the primary processing of airline passenger data, data structuring and further clustering,
taking into account industry specifics. Materials and methods. To solve this problem, the best
practices of building loaded systems for working with big data were studied, the most promising
from the point of view of development and mutual integration were identified. Results. The architecture of the passenger clustering system chosen as a result of the work was successfully
implemented in practice and proved to be effective and reliable. Conclusions. The
described approach is recommended for use as well-proven in working with large arrays of
industrial data. The approach will allow flexible scaling of the data processing system and
connection of other modules to it in the future.
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