Question

What compromise approach is suggested for the level of granularity in the data warehouse for data mining engagements?

a.

Store only light summaries

b.

Strive to store detailed data unless it's a burden

c.

Extract detailed data directly from operational systems

d.

Only keep high-level summaries

Posted under Data Warehousing and OLAP

Answer: (b).Strive to store detailed data unless it's a burden Explanation:It is suggested to strive to store detailed data unless it is a huge burden, as detailed data is essential for data mining engagements.

Engage with the Community - Add Your Comment

Confused About the Answer? Ask for Details Here.

Know the Explanation? Add it Here.

Q. What compromise approach is suggested for the level of granularity in the data warehouse for data mining engagements?

Add Comment

Similar Questions

Discover Related MCQs

Q. What is the relationship between data mining algorithms and data mining techniques?

View solution

Q. How are data mining processes related to data mining applications?

View solution

Q. What is clustering in the context of data mining?

View solution

Q. How is cluster detection characterized in terms of knowledge discovery?

View solution

Q. In cluster detection, what is the role of variables like age group and income level?

View solution

Q. What is the purpose of forming clusters in data mining?

View solution

Q. What is essential for understanding and utilizing the clusters formed by the data mining algorithm?

View solution

Q. In the context of data mining, what is K in the K-means clustering algorithm?

View solution

Q. How does the K-means clustering algorithm initially choose centroids?

View solution

Q. What determines the closeness of a customer record to a centroid in the K-means clustering algorithm?

View solution

Q. How does the algorithm redraw cluster boundaries in the K-means clustering algorithm?

View solution

Q. What is the primary application of decision trees in data mining?

View solution

Q. Why might decision trees be suitable in cases where the reasons for predictions are important?

View solution

Q. How is the effectiveness of a decision tree measured?

View solution

Q. What does pruning aim to achieve in decision trees?

View solution

Q. In memory-based reasoning (MBR), what does the algorithm use to predict unknown instances?

View solution

Q. What does the distance function do in MBR?

View solution

Q. What is the key role of the combination function in MBR?

View solution

Q. In MBR, what does the nearest neighbor predict for unknown respondents?

View solution

Q. What are the three critical issues when solving a data mining problem using MBR?

View solution

View All MCQs on Data Warehousing and OLAP

Suggested Topics

Are you eager to expand your knowledge beyond Data Warehousing and OLAP? We've curated a selection of related categories that you might find intriguing.

Click on the categories below to discover a wealth of MCQs and enrich your understanding of Computer Science. Happy exploring!

Java Programming

Level up your coding skills with our Java Programming MCQs. From object-oriented...

MySQL Database

Enhance your knowledge of relational databases with our MySQL MCQs. Understand...

DBMS

Get a firm grasp on database systems with our DBMS MCQs. Explore relational...

Data Warehousing and OLAP

Strengthen your knowledge of Data Warehousing and OLAP with our specialized MCQs....

Python

Dive into one of the most popular languages with our Python MCQs. Understand...

CompTIA PenTest+ Certification Exam PT0 002

Prepare for the CompTIA PenTest+ PT0-002 exam with our targeted MCQs. Covering...

Systems Analysis and Design Methods

Get familiar with the process of designing and improving business systems with our...

Computer Hardware

Explore the tangible components of computers with our Computer Hardware MCQs. Learn...

Data Structures and Algorithms

Journey through the fundamentals of Data Structures and Algorithms with our extensive...