adplus-dvertising
frame-decoration

Question

In the context of business analytics, why is changing the processing paradigm considered important?

a.

To ensure efficient utilization of resources

b.

To allow for more scalability with Big Data clusters

c.

To reduce the need for data indexing

d.

To provide fast answers and avoid wasting time

Posted under Big Data Computing

Answer: (d).To provide fast answers and avoid wasting time Explanation:Changing the processing paradigm in business analytics is important because it allows for fast answers and avoids wasting time, especially in situations where answers are needed quickly.

Engage with the Community - Add Your Comment

Confused About the Answer? Ask for Details Here.

Know the Explanation? Add it Here.

Q. In the context of business analytics, why is changing the processing paradigm considered important?

Similar Questions

Discover Related MCQs

Q. What is the primary purpose of data exploration in the context of query processing for Big Data?

Q. What is a common characteristic of scenarios where data exploration is needed?

Q. How should next-generation database systems interpret queries?

Q. What is the key benefit of systems that support data exploration?

Q. What major costs can exploration-based systems help avoid?

Q. What is the primary goal of an efficient data exploration system?

Q. What does the system need to remember in order to guide the user effectively in data exploration?

Q. What is the purpose of adaptive indexing?

Q. What is the primary purpose of adaptive indexing?

Q. What is the main problem with the set of potential indices in database systems?

Q. How has the complexity of index selection in database systems changed over time?

Q. What is required for offline indexing to make tuning choices and perform tuning actions?

Q. In dynamic environments with Big Data, what are described as scarce resources?

Q. What approach was introduced to address the physical design problem in databases?

Q. How does database cracking differ from traditional indexing in terms of index creation?

Q. How is every query treated in the context of database cracking?

Q. What is the primary data storage representation used in column-store databases?

Q. How does a column store's data access during query processing differ from traditional row stores?

Q. What kind of processing do column stores typically rely on?

Q. What does the term "cracking" in the context of database cracking reflect?