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Answer: Collect and clean the data to ensure accuracy, then use statistical methods to identify patterns and trends in production efficiency, followed by a root cause analysis for any inefficiencies identified.
Option C is the most appropriate answer as it comprehensively addresses the need for descriptive and diagnostic analytics by ensuring data accuracy through collection and cleaning, identifying patterns and trends with statistical methods, and understanding the root causes of inefficiencies. This approach aligns with the company's concerns for cost efficiency, compliance, and scalability. Options A, B, and D either overlook critical steps in the analytics process or prioritize speed over accuracy and depth of analysis.
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As a Microsoft Fabric Analytics Engineer Associate, you are tasked with implementing descriptive and diagnostic analytics for a manufacturing company to identify potential areas for process improvement. The company is concerned with cost efficiency, compliance with industry standards, and scalability of the solution. Which of the following steps would you take to ensure the analytics solution meets these requirements? Choose the best option.
A
Immediately deploy a predictive model to forecast future production levels without preliminary data analysis, to save time and resources.
B
Visualize the data using basic charts like bar and pie charts for a quick overview, then proceed to develop a predictive model without further analysis.
C
Collect and clean the data to ensure accuracy, then use statistical methods to identify patterns and trends in production efficiency, followed by a root cause analysis for any inefficiencies identified.
D
Skip the data collection and cleaning phase, and directly perform a root cause analysis based on assumptions to quickly address potential inefficiencies.
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