DWM Quiz 1 (24-25)

1.Which of the following best describes the primary difference between the Star Schema and the Snowflake Schema in dimensional modeling?

• A) The Star Schema contains normalized dimension tables, while the Snowflake Schema has denormalized dimension tables.

• B) The Star Schema uses a central fact table connected to dimension tables, whereas the Snowflake Schema features a central fact table with normalized, hierarchical dimension tables.

• C) The Snowflake Schema is used primarily for OLTP systems, while the Star Schema is designed for OLAP systems.

• D) The Star Schema supports only simple aggregations, while the Snowflake Schema supports complex aggregations.

2. 2. What is the primary characteristic that distinguishes MOLAP from ROLAP and HOLAP in OLAP systems?

• A) MOLAP uses multidimensional cubes to store data, while ROLAP uses relational databases and HOLAP combines both methods.

• B) MOLAP supports a higher degree of data normalization compared to ROLAP.

• C) ROLAP is designed for faster query processing compared to MOLAP.

• D) HOLAP provides a more detailed data view compared to MOLAP and ROLAP.

3. 3. In the context of OLAP operations, which operation is best described by the process of aggregating data along different dimensions to provide summarized information?

• A) Slice

• B) Dice

• C) Roll-up

• C) Roll-up

4. 4. In the Knowledge Discovery in Databases (KDD) process, what is the primary role of data cleaning?

• A) To integrate data from multiple sources into a unified format.

• B) To remove or correct inaccuracies and inconsistencies in the data.

• C) To summarize data using statistical techniques.

• D) To select a subset of attributes for further analysis.

5. 5.Which type of attribute is characterized by having a finite number of distinct values, where each value represents a category or label?

• A) Continuous Attribute

• B) Nominal Attribute

• C) Ordinal Attribute

• D) Ratio Attribute

6.In data mining, what is the significance of measuring similarity and dissimilarity between data objects?

• A) It helps in identifying redundant data and removing duplicates.

• B) It is crucial for clustering and classification tasks to group similar items and distinguish between different categories.

• C) It is used to generate visualizations of data trends over time.

• D) It assists in converting data into a format suitable for storage.

7.In Decision Tree Induction, which of the following is the primary attribute selection measure used to determine the best split at a node?

• A) Chi-square

• B) Gini Index

• C) Entropy

• D) Information Gain

8.In Naïve Bayes Classification, which assumption is made about the features?

• A) Features are highly correlated with each other.

• B) Features are conditionally independent given the class label.

• C) Features are not independent and have a hierarchical structure.

• D) Features are dependent on previous features in a sequential manner.

9.Which measure is used to evaluate the performance of a classification model by indicating the proportion of true positive instances among all positive instances predicted by the model?

• A) Precision

• B) Recall

• C) F1 Score

• D) Accuracy

10.Which of the following techniques is used for data reduction by summarizing data into a smaller representation, often through aggregating values?

• A) Sampling

• B) Attribute Subset Selection

• C) Clustering

• D) Histogram Analysis