NCA-GENL Question 120
Select 3A data science team is analyzing a large dataset of customer interactions to identify trends that improve customer satisfaction. They aim to use data mining and visualization techniques to extract actionable insights. Which of the following steps are critical to achieving this goal effectively?
- A
Preprocessing the data to handle missing values and outliers
- B
Using data visualization to identify patterns and correlations in the dataset
- C
Performing random sampling without understanding the data distribution
- D
Applying clustering techniques to group similar customer behaviors
- E
Ignoring data outliers to avoid skewing the results
Show answer and explanation
Correct answers: A, B, D
Explanation
To extract actionable insights from large datasets, preprocessing the data ensures accuracy, data visualization reveals patterns, and clustering techniques help to group similar behaviors for better understanding. Neglecting proper sampling or ignoring outliers, however, can result in misleading conclusions or missed opportunities.
- A. Correct.
Preprocessing the data is a critical step to clean and prepare it for analysis, ensuring more accurate and reliable insights.
- B. Correct.
Data visualization helps to uncover patterns and trends in the dataset, which can guide further analysis and decision-making.
- C. Incorrect.
Random sampling without understanding the data distribution can lead to biased or incomplete insights, making this an ineffective approach.
- D. Correct.
Clustering techniques are useful for grouping similar behaviors or patterns, which can be an important step in data mining for insights.
- E. Incorrect.
Ignoring outliers may lead to the loss of valuable information or trends, especially if the outliers represent uncommon but impactful customer behaviors.