NCA-GENL Question 16
Select 3A data science team is tasked with analyzing a large dataset of customer reviews to identify trends in customer sentiment. They decide to use data mining and data visualization techniques to extract insights. Which of the following steps are most relevant to this process?
- A
Preprocessing the dataset to remove duplicate or irrelevant data
- B
Training a deep learning model before any data exploration
- C
Using clustering algorithms to group similar customer sentiments
- D
Creating visualizations like word clouds or sentiment trend graphs
- E
Applying gradient descent optimization to improve visualization quality
Show answer and explanation
Correct answers: A, C, D
Explanation
Extracting insights from large datasets involves a combination of preprocessing, data mining techniques like clustering, and data visualization to uncover and communicate patterns. Training models or applying optimization methods is outside the scope of the described process, as the focus is on exploration and understanding rather than prediction or optimization.
- A. Correct.
Preprocessing ensures the dataset is clean and relevant, which is a critical first step in extracting meaningful insights from data.
- B. Incorrect.
Training a model is not directly relevant to the described process, as the focus is on exploration and visualization rather than predictive modeling.
- C. Correct.
Clustering algorithms can help identify patterns in customer sentiment, making it an important step in data mining.
- D. Correct.
Visualizations like word clouds or trend graphs are essential tools for interpreting and communicating insights from the data.
- E. Incorrect.
Gradient descent optimization is a machine learning technique and is unrelated to data visualization or mining in this context.