A Unified MLOps and Data Architecture Blueprint for CrossEnterprise Decisioning in Global Financial and Tourism Ecosystems
DOI:
https://doi.org/10.15662/fvfbvw31Keywords:
Tourism, MLOps, Cross-Enterprise, Finance, Data ArchitectureAbstract
This study has outlined the factors where the individual MLOps and data architecture could improve operational efficiency, model performance, and cross domain business decision making in the financial and tourism business. The paper compares traditional silo-based systems to the typical Feature Store, frequent model contracts and a Model-as-a-Service implementation plan. It is also reported to have quantitatively enjoyed high feature reuse gains, reduced manual work, reduced pipeline failures and reduced deployment cycles. The integrated system also increases the speed of inferences and predictability of the different business units. The implication of these findings is that there is a possibility of scaling the machine learning, and overall quality of the decisions made by using a common
architecture in large organizations
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