This thesis delves into several methodologies for Hierarchical Data Forecasting and compares their usage in the Business sector. It assesses the approaches through analysis of performance and compares them to shed light on the most effective choice for businesses. Ultimately, it offers valuable insights into leveraging hierarchical data for informed business decisions in an increasingly competitive landscape, showcasing the potential for enhanced strategic planning and competitive advantage.
This thesis delves into several methodologies for Hierarchical Data Forecasting and compares their usage in the Business sector. It assesses the approaches through analysis of performance and compares them to shed light on the most effective choice for businesses. Ultimately, it offers valuable insights into leveraging hierarchical data for informed business decisions in an increasingly competitive landscape, showcasing the potential for enhanced strategic planning and competitive advantage.
Hierarchical Data Forecasting for the Business Sector
SVEÇLA, ENDRIT
2023/2024
Abstract
This thesis delves into several methodologies for Hierarchical Data Forecasting and compares their usage in the Business sector. It assesses the approaches through analysis of performance and compares them to shed light on the most effective choice for businesses. Ultimately, it offers valuable insights into leveraging hierarchical data for informed business decisions in an increasingly competitive landscape, showcasing the potential for enhanced strategic planning and competitive advantage.File | Dimensione | Formato | |
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Hierarchical_Data_Forecasting_for_the_Business_Sector.pdf
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4.07 MB
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https://hdl.handle.net/20.500.12608/62029