NCA-GENL Question 18
Select 3A data science team is tasked with analyzing a massive dataset containing customer reviews to understand key trends and insights. They decide to use data visualization and data mining techniques. Which of the following steps are most relevant to this process?
- A
Using clustering algorithms to group similar customer reviews
- B
Creating scatter plots and heatmaps to identify patterns in the data
- C
Applying a generative AI model to synthesize new customer reviews
- D
Cleaning and preprocessing the dataset to handle missing or inconsistent data
- E
Deploying the insights directly into a production environment without validation
Show answer and explanation
Correct answers: A, B, D
Explanation
The process of extracting insights from large datasets involves a combination of data mining techniques (e.g., clustering), data visualization methods (e.g., scatter plots, heatmaps), and data preprocessing (e.g., cleaning). These steps ensure the data is structured and patterns are clearly identified, enabling meaningful analysis. However, steps like generating new data or skipping validation are outside the scope of extracting insights and do not align with best practices.
- A. Correct.
Clustering algorithms are a key data mining technique for grouping similar data points, which is essential for identifying trends in customer reviews.
- B. Correct.
Scatter plots and heatmaps are visualization tools that help in identifying patterns and trends in large datasets, making them highly relevant to this task.
- C. Incorrect.
While generative AI models can synthesize new data, this step does not directly contribute to extracting insights from the original dataset.
- D. Correct.
Data cleaning and preprocessing are crucial for ensuring the quality of the dataset, which is a foundational step in any analysis process.
- E. Incorrect.
Deploying insights without validation is not a recommended practice, as it risks propagating incorrect or incomplete conclusions.