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Exam MB-330 topic 6 question 35 discussion

Actual exam question from Microsoft's MB-330
Question #: 35
Topic #: 6
[All MB-330 Questions]

DRAG DROP
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A company is implementing Dynamics 365 Supply Chain Management.

The company requires that historical transactional data from the current system be used to determine future inventory needs. Transactions that fall outside of a standard deviation must be excluded.

You need to configure the system to meet the requirements.

What should you configure? To answer, drag the appropriate configurations to the correct requirements. Each configuration may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.

NOTE: Each correct selection is worth one point.

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globeearth
2 days ago
[1] Demand forecasting in D365 allows the system to analyze historical transactional data (e.g., sales orders, inventory movements) to predict future inventory needs. It uses this data to generate demand forecasts, which can then be integrated into master planning to determine inventory requirements. [2] Demand forecasting, D365 provides tools to refine forecasts by filtering outliers, such as transactions that fall outside a standard deviation. When configuring demand forecasting parameters (e.g., via the Demand forecasting parameters setup or the forecasting model in Azure Machine Learning), you can adjust settings to exclude anomalies based on statistical measures like standard deviation.
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Blesaf
5 months, 3 weeks ago
Correct Demand forecasting for both, please have in mind the following: Safety stock journal does not use historical transactional data to define future inventory, nor does it exclude transactions outside of a standard deviation. It only lets you adjust the safety stock quantity for items in a warehouse.
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TPST
6 months, 2 weeks ago
Should be Demand Forecasting for both 1. "Demand forecasting is used to predict independent demand from sales orders and dependent demand at any decoupling point for customer orders. The enhanced demand forecast reduction rules provide an ideal solution for mass customization. To generate the baseline forecast, a summary of historical transactions is passed to Microsoft Azure Machine Learning hosted on Azure." https://learn.microsoft.com/en-us/dynamics365/supply-chain/master-planning/introduction-demand-forecasting 2. Remove outliers from historical transaction data when calculating a demand forecast https://learn.microsoft.com/en-us/dynamics365/supply-chain/master-planning/remove-historical-outliers-calculating-demand-forecast
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