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Cattel Sales Forecast Project

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    Year of implementation
    2024
    Industry
    Retail

    Review of Artificial Intelligence algorithms and DevOps processes for a short/medium-term sales forecasting project of fish stock.

    Approach and methodology

    We adopted a modular approach, revising the architecture to separate the forecasting and infrastructure components. After an analysis, the algorithms were optimized for greater accuracy and integrated with pipelines and DevOps (with IaC) for continuous cloud deployment, improving scalability, reliability, and computing speed.

    Staff involved in the project
    3 Specialists
    Execution time
    5 Months
    Technologies used
    • Amazon Web Services (AWS)
    • AWS Forecast
    • AWS Lambda
    • AWS Step Functions
    • NumPy
    • Panda
    • Python
    30
    %
    Improvement in forecast accuracy (WAPE)
    Increase in data flows managed simultaneously
    -66
    %
    Cost reduction

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