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In this tutorial, the speaker analyzes sales data categorized into A, B, and C to determine appropriate forecasting methods using multiple models. They emphasize the importance of understanding data distribution by assessing skewness, which indicates the variation in the dataset. A low skewness suggests minimal variation, making forecasting simpler, while significant skewness may complicate predictions due to internal variations. The tutorial aims to help viewers understand how to evaluate data characteristics to enhance forecasting accuracy.