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Answer: Apply optimization algorithms to calculate the optimal inventory levels for each product, taking into account factors such as demand variability, holding costs, and the risk of stockouts, to provide prescriptive recommendations for inventory management.
Option D is the correct answer because it directly addresses the need for prescriptive analytics by applying optimization algorithms to determine the optimal inventory levels. This approach not only analyzes the data but also provides actionable recommendations that consider critical factors like demand variability and holding costs, which are essential for efficient inventory management. While options A, B, and C offer valuable insights through predictive analytics, they do not provide the prescriptive recommendations required to optimize inventory levels effectively.
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As a Microsoft Fabric Analytics Engineer Associate, you are tasked with integrating prescriptive analytics into a visual report for a retail company to optimize their inventory management. The company has provided a dataset containing product sales and inventory levels over the past year. Your goal is to recommend the most effective approach to not only analyze the data but also to provide actionable insights that can lead to cost savings and improved inventory turnover. Considering the need for a solution that accounts for demand variability, holding costs, and the risk of stockouts, which of the following approaches would you choose? (Choose one option)
A
Implement a regression analysis to understand the relationship between product sales and various influencing factors, then visualize these relationships using a scatter plot to identify trends.
B
Develop a classification model to categorize products based on their likelihood of going out of stock, and use a confusion matrix to visualize the model's accuracy in predicting stockouts.
C
Conduct a time series analysis to forecast future product sales based on historical data, and present the forecasted sales trends using a line chart for easy interpretation.
D
Apply optimization algorithms to calculate the optimal inventory levels for each product, taking into account factors such as demand variability, holding costs, and the risk of stockouts, to provide prescriptive recommendations for inventory management.