Data Warehousing and Data Mining MCQ Quiz with Answers

Data Warehousing and Data Mining MCQ Quiz with Answers

Data Warehousing and Data Mining MCQ Quiz with Answers. Data mining and data warehousing multiple choice questions with answers pdf.

Are you looking to test your knowledge on Data Warehousing and Data Mining? If so, then you have come to the right place. This article provides a comprehensive MCQ quiz with answers that are designed to help you enhance your knowledge of the topics.

The quiz consists of questions specifically tailored to cover the fundamental concepts around Data Warehousing and Data Mining. In addition, this article provides detailed explanations for each answer so that you can gain a better understanding of the topics.

Data Warehousing

What is Data Warehousing and Data Mining

Data warehousing and data mining are two important concepts in the field of information technology. Data warehousing is a process that involves collecting, storing, and managing large amounts of data in a centralized location.

This data can come from various sources such as customer transactions, employee records, and sales data. The goal of data warehousing is to provide an efficient way to store and manage this information so it can be easily accessed by users.

On the other hand, data mining involves analyzing this stored data to extract meaningful insights and patterns. Data mining techniques use statistical algorithms and machine learning tools to identify patterns within the stored data.

These patterns can be used to make more informed business decisions or predict future trends. Data mining is commonly used in industries such as finance, healthcare, and retail for fraud detection, risk management, and targeted marketing campaigns.

Data Warehousing and Data Mining MCQs

1. Data Mining is also referred to as ___.
a. Knowledge discovery in databases
b. Data Cleaning
c. Data extraction
d. Data management
Ans: A

2. Oracle 10 g provides software called ___, which is a data mining tool.
a. Data miner 10g
b. Dolphin
c. Data miner
d. Darwin
Ans: D

3. Data about data is called ___.
a. Table
b. Database
c. Metadata
d. Integration
Ans: C

4. To represent any n–Dimension data we need a series of ___ Dimension cubes.
a. (n–1)
b. n
c. n+1
d. n+2
Ans: A

5. Which of the following schema contains multiple fact tables?
a. Star schema
b. Snowflake schema
c. Fact constellation
d. None of the above
Ans: C

6. The ___ operation performs a selection on one dimension of the given cube, resulting in a subcube.
a. Pivot
b. Slice
c. Roll-up
d. Drill – down
Ans: B

7. ___ servers support multidimensional views of data through array-based multidimensional storage engines.
a. ROLAP
b. MOLAP
c. Data warehouse
d. Database
Ans: B

8. ___ is used to refer to systems and technologies that provide the business with the means for decision-makers to extract personalized meaningful information about their business and industry.
a. Business intelligence
b. Data warehouse
c. Database
d. All the above
Ans: A

9. The ___ software gives the user the opportunity to look at the data from a variety of different dimensions.
a. Query Tools
b. Multidimensional Analysis Software
c. Data Mining Tools
d. None of the above
Ans: B

10. Which of the following layer is concerned with producing metadata about the ETL process?
a. Data integration layer
b. Applications layer
c. Access layer
d. None of the above
Ans: A

11. ___ methods smooth a sorted data value by consulting its “neighborhood”, that is, the values around it.
a. Binning
b. Clustering
c. Combined computer and human inspection
d. Regression
Ans: A

12. ___ techniques can be used to reduce the number of values for a given continuous attribute, by dividing the range of the attribute into intervals.
a. Discretization
b. Transformation
c. Smoothing
d. Generalization
Ans: C

13. ___ can be used to help avoid errors in schema integration.
a. User data
b. System administrator
c. Metadata
d. All the above
Ans: C

14. A frequent set is a ___ if it is a frequent set and no superset of this is a frequent set.
a. Border set
b. Minimal frequent set
c. Maximal frequent set
d. None of the above
Ans: C

15. ___ is the oldest and most well-known statistical technique that the Data Mining community utilizes.
a. Regression
b. Clustering
c. Decision Trees
d. None of the above
Ans: A

16. An ___ is an information-processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information.
a. Decision tree
b. Prediction network
c. Artificial Neural Network
d. All the above
Ans: C

17. FP–Tree Growth Algorithm can be implemented in ___ Phases.
a. One
b. Two
c. Three
d. Four
Ans: B

18. The pincer–search algorithm is based on ___ search.
a. Bi-directional
b. Single-directional
c. Random
d. Sequential
Ans: A

19. ___ algorithm works like a train running over the data, with stops at intervals M between transactions. When the train reaches the end of the transaction file it completes one path.
a. FP–Tree Growth
b. Partition Algorithm
c. Dynamic Itemset Counting
d. Pincers – Search
Ans: C

20. It is difficult to find strong associations among data items at low or primitive levels of abstraction due to the ___ of data in multidimensional space.
a. Sparsity
b. Scarcity
c. Plenty
d. Excess
Ans: A

21. The process of partitioning the ranges of quantitative attributes into intervals is called ___.
a. Splitting
b. Grouping
c. Binning
d. None of the above
Ans: C

22. ___ attributes are numeric and have an implicit ordering among values.
a. Quantitative
b. Nominal
c. Categorical
d. None of the above
Ans: A

23. In the K-means clustering algorithm the distance between cluster centroid to each object is calculated using the ___ method.
a. Euclidean distance
b. Clustering distance
c. Central distance
d. Cluster width
Ans: A

24. ___ techniques are more commonly used in hierarchical clustering and this is the method implemented in XLMiner™.
a. Agglomerative
b. Divisive
c. K-means
d. None of the above
Ans: A

25. Hierarchical clustering may be represented by a two-dimensional diagram known as ___.
a. Dendrogram
b. Cladogram
c. Histogram
d. None of the above
Ans: A

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