Abstract: Various examples described herein support or provide for data ingesting, aggregating, and organizing in one centralized location; enhancing data through data enrichment and artificial intelligence and machine learning automation into tailored recommendations; and distributing and integrating data into channels that help facilitating data exchange based on individual needs and/or third-party solutions.

Abstract: Methods and systems for demand forecasting are provided. Historical demand data for a related product is acquired. The historical demand data corresponds to a period of time during which a promoted product was promoted. The demand effect of the related product is determined during this period of time and used to project or forecast a demand for the related product when the promoted product is subsequently promoted. The demand effect can be positive or negative. A positive demand effect identifies an affinity relationship between the promoted product and the related product. A negative demand effect identifies a cannibalization relationship between the promoted product and the related product.