
Answer-first summary for fast verification
Answer: Filter data by DefectRate and analyze correlations with other variables using heat maps.
Diagnostic analytics involves identifying correlations between defect rates and other variables. Using SQL to filter data by DefectRate and analyzing these correlations with heat maps provides a clear visualization of which factors are most strongly associated with high defect rates.
Author: LeetQuiz Editorial Team
Ultimate access to all questions.
No comments yet.
In your role, you need to implement diagnostic analytics to understand the reasons behind high defect rates in a manufacturing company. The dataset includes 'ProductID', 'ProductionDate', 'Quantity', 'MachineID', and 'DefectRate'. Describe how you would use SQL queries and data visualization tools in Microsoft Fabric to identify key factors contributing to defects. Include the types of analyses you would perform and the visualizations that would best represent these findings.
A
Use SQL to group data by MachineID and ProductionDate, then use pie charts for visualizations.
B
Aggregate data by Quantity and DefectRate, then use bar charts and line charts for visualizations.
C
Filter data by DefectRate and analyze correlations with other variables using heat maps.
D
Sort data by ProductID and use scatter plots for visualizations.