MLS-C01 Question #182: Real Exam Question with Answer & Explanation

Question

A company supplies wholesale clothing to thousands of retail stores. A data scientist must create a model that predicts the daily sales volume for each item for each store. The data scientist discovers that more than half of the stores have been in business for less than 6 months. Sales data is highly consistent from week to week. Daily data from the database has been aggregated weekly, and weeks with no sales are omitted from the current dataset. Five years (100 MB) of sales data is available in Amazon S3. Which factors will adversely impact the performance of the forecast model to be developed, and which actions should the data scientist take to mitigate them? (Choose two.)

Options

• ADetecting seasonality for the majority of stores will be an issue. Request categorical data
• BThe sales data does not have enough variance. Request external sales data from other
• CSales data is aggregated by week. Request daily sales data from the source database to
• DThe sales data is missing zero entries for item sales. Request that item sales data from
• EOnly 100 MB of sales data is available in Amazon S3. Request 10 years of sales data,