Data Mining Objective Questions and Answers for MCA, BCA

Data Mining Objective Questions and Answers for MCA, BCA

Data Mining Objective Questions and Answers for MCA, BCA. Data mining is MCQ. Data Warehousing and Data Mining objective type questions.

Are you looking for 50 Data Mining Objective Questions and Answers? If so, you’ve come to the right place! This is an important skill to have in today’s digital world, and this article will provide you with all the questions and answers you need.

Whether you’re a student studying for a data-mining exam or a professional brushing up on your skills, these questions and answers are sure to be helpful.

Data Mining

What is Data Mining

Data mining is the process of discovering patterns and relationships within large sets of data. It involves using advanced algorithms and computational techniques to extract valuable insights from vast amounts of information. The goal is to uncover hidden patterns, trends, and correlations that can be used to make better business decisions.

Data mining has been used in a variety of industries, from finance and healthcare to retail and marketing. It allows businesses to analyze customer behavior, optimize marketing campaigns, identify fraud or anomalies in financial transactions, and even predict future trends based on historical data.

By leveraging the power of data mining techniques, organizations can gain a competitive advantage by making informed decisions that are backed by quantitative evidence.

However, there are some concerns surrounding data mining as well. Privacy issues arise when personal information is collected without consent or improperly secured. Additionally, there may be ethical implications regarding how the insights gained through datamining are used.

50 Data Mining Objective Questions and Answers

1. Typical techniques for data mining involve ___.
A. Decision trees
B. Neural networks
C. Genetic algorithms
D. All of the above
Ans: D

2. POS collects the information on the item ___.
A. Brand name
B. Size
C. Category
D. All of the above
Ans: D

3. Which of the following industries use data mining techniques?
A. Chemical
B. Finance
C. Marketing
D. None of the above
Ans: B

4. ___ is the process of analyzing data from different perspectives and summarizing it into useful information.
A. Data process
B. Data management
C. Data mining
D. Database management
Ans: C

5. ___ data is included in the transactional data.
A. Sales
B. Cost
C. Inventory
D. All of the above
Ans: D

6. Data warehousing deals with the subjects’ like ___.
A. Supplier
B. Product
C. Sales
D. A, B, and C
Ans: D

7. ___operation is used by the data warehousing in accessing data.
A. Data control
B. Data access
C. Data mining
D. Data processing
Ans: B

8. Data warehousing brings ___ performance to the integrated heterogeneous database system.
A. High
B. Low
C. Moderate
D. Very less
Ans: A

9. Which of the following encompasses a broad range of analytical software and provide the solution for gathering information?
D. None of the above
Ans: B

10. Identify business intelligence tools from the following.
B. Data mining tools
C. Query tools
D. All of the above
Ans: D

11. Data cleaning helps to fill ___values.
A. Missing
B. Routine
C. Old
D. New
Ans: A

12. Data mining techniques are classified based on ___.
A. Database
B. Knowledge to be discovered
C. Techniques to be utilized
D. All of the above
Ans: D

13. ___ software provides the ability to store, access, and modify the data.
C. Data warehousing
D. None of the above
Ans: A

14. ___ Language is supported by DBMS.
A. C++
B. Query
C. C
D. Java
Ans: B

15. Detecting anomalies is a___ technique.
A. Data warehousing
B. Data stage
C. Data mining
D. Data cleaning
Ans: C

16. Identify data mining techniques from the following.
A. Clustering
B. Data summarization
C. Classification
D. All of the above
Ans: D

17. ___ can manage the data on physical storage devices.
A. Data stage
C. Data mining
D. Data warehousing
Ans: B

18. Who proposed priori algorithm?
A. Agarwal
B. Srikanth
C. Srikaran
D. Agarwal and Srikanth
Ans: D

19. ___ rule can describe associations between quantitative items or attributes.
A. Qualitative
B. Quantitative
C. Multilevel
D. Multidimensional
Ans: B

20. Identify the prediction technique from the following.
A. Nearest neighbor
B. Clustering
C. Data mining
D. Data warehousing
Ans: A

21. Identify a link analysis algorithm from the following.
A. Web Agent
B. Page rank
C. Page view
D. None of the above
Ans: B

22. ___ Approach mainly concentrates on improving information finding and filtering.
A. Agent-based approach
B. Database approach
C. Attribute selection approach
D. Testing approach
Ans: A

23. Which of the following system can store and manage a large collection of multimedia data?
C. Multimedia database
Ans: C

24. ___ are the queries of the content-based image retrieval system.
A. Image sample-based queries
B. Image feature specification queries
C. Both a and b
D. Image sample specification queries
Ans: C

25. ___strategy has the capacity to reduce the overall data mining cost without loss of quality.
A. Resolution
B. Mining
C. Multi-resolution mining
D. Multiresolution
Ans: C

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