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As a Microsoft Fabric Analytics Engineer Associate, you are tasked with profiling a dataset of online advertising click-through rates to optimize future advertising campaigns. The dataset includes information on user demographics, ad content, and click-through rates. Your analysis must consider data quality, user engagement patterns, and the potential for scaling the analysis across multiple campaigns. Which of the following approaches provides the most comprehensive analysis to identify factors that significantly influence click-through rates? (Choose one option.)
A
Calculate the average click-through rate for each advertising campaign and visualize the results using a bar chart to compare performance across campaigns.
B
Perform a cohort analysis to compare click-through rates across different user segments, such as age or gender, and identify trends over time.
C
Use natural language processing techniques to analyze the content of advertising headlines and identify patterns that are more likely to drive user engagement, alongside assessing data quality issues.
D
Perform a data quality assessment to identify missing values, duplicates, and inconsistencies in the dataset, ensuring the reliability of the analysis.