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Answer: Aggregate data by Date and SalesAmount, then use bar charts and line charts for visualizations.
Exploratory analytics in retail involves aggregating data by key variables like Date and SalesAmount to identify patterns. Bar charts and line charts are effective for visualizing these relationships, helping to uncover insights that could improve sales strategies.
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You have been given a dataset from a retail company containing sales data with fields such as 'Date', 'StoreID', 'ProductID', 'SalesAmount', and 'PromotionFlag'. Your task is to perform exploratory analytics to uncover patterns and insights that could improve sales strategies. Describe the steps you would take, including the types of analyses you would perform and the visualizations you would use in Microsoft Fabric to represent your findings.
A
Use SQL to group data by StoreID and ProductID, then use pie charts for visualizations.
B
Aggregate data by Date and SalesAmount, then use bar charts and line charts for visualizations.
C
Filter data by PromotionFlag and analyze correlations with other variables using heat maps.
D
Sort data by Date and use scatter plots for visualizations.