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Welcome to the Big Data Exploration MCQs Page

Dive deep into the fascinating world of Big Data Exploration with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Big Data Exploration, a crucial aspect of Big Data Computing. In this section, you will encounter a diverse range of MCQs that cover various aspects of Big Data Exploration, from the basic principles to advanced topics. Each question is thoughtfully crafted to challenge your knowledge and deepen your understanding of this critical subcategory within Big Data Computing.

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Check out the MCQs below to embark on an enriching journey through Big Data Exploration. Test your knowledge, expand your horizons, and solidify your grasp on this vital area of Big Data Computing.

Note: Each MCQ comes with multiple answer choices. Select the most appropriate option and test your understanding of Big Data Exploration. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

Big Data Exploration MCQs | Page 2 of 9

Explore more Topics under Big Data Computing

Q11.
Why is energy consumption considered a critical side effect of dealing with Big Data?

a.

Because modern telescopes consume a lot of energy

b.

Because energy consumption is a new problem introduced by Big Data

c.

Because more data requires more energy to process

d.

Because high-performance computing reduces energy consumption

Discuss
Answer: (b).Because energy consumption is a new problem introduced by Big Data Explanation:Energy consumption is considered a critical side effect of dealing with Big Data.
Q12.
Why does the query-processing paradigm need to change with more data?

a.

To ensure processing of all available data

b.

To reduce energy consumption

c.

Because past solutions are still effective

d.

Because processing all data is not possible or necessary

Discuss
Answer: (d).Because processing all data is not possible or necessary Explanation:With more data, the query-processing paradigm needs to change because processing all data is not possible or necessary.
Q13.
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

Discuss
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.
Q14.
What is the primary purpose of data exploration in the context of query processing for Big Data?

a.

To guarantee complete and correct answers to user queries

b.

To facilitate instant data analysis without user interaction

c.

To assist users in discovering interesting patterns when the exact query is unknown

d.

To enforce strict contracts for database usage

Discuss
Answer: (c).To assist users in discovering interesting patterns when the exact query is unknown Explanation:Data exploration in the context of query processing for Big Data is primarily about assisting users in discovering interesting patterns when the exact query is unknown.
Q15.
What is a common characteristic of scenarios where data exploration is needed?

a.

A daily stream of Big Data

b.

A focus on achieving complete and correct answers

c.

Slow and infrequent data updates

d.

Predictable user behavior patterns

Discuss
Answer: (a).A daily stream of Big Data Explanation:Scenarios requiring data exploration often involve a daily stream of Big Data, typically in the order of multiple terabytes.
Q16.
How should next-generation database systems interpret queries?

a.

As contracts that cannot be modified

b.

By their intent, rather than as rigid contracts

c.

With a focus on instant data processing

d.

With a primary goal of guaranteeing complete answers

Discuss
Answer: (b).By their intent, rather than as rigid contracts Explanation:Next-generation database systems should interpret queries by their intent, rather than as rigid contracts.
Q17.
What is the key benefit of systems that support data exploration?

a.

Ensuring complete and correct answers to all queries

b.

Minimizing the need for incremental data updates

c.

Guiding users toward a predefined path for data analysis

d.

Allowing incremental and adaptive exploration of data

Discuss
Answer: (d).Allowing incremental and adaptive exploration of data Explanation:The key benefit of systems supporting data exploration is allowing incremental and adaptive exploration of data, which helps avoid major inherent costs associated with processing large data sets.
Q18.
What major costs can exploration-based systems help avoid?

a.

Costs related to enforcing strict contracts for database usage

b.

Costs associated with data analysis in the context of data exploration

c.

Costs of numerous procedures, steps, and algorithms in data management systems

d.

Costs of processing data updates in real-time

Discuss
Answer: (c).Costs of numerous procedures, steps, and algorithms in data management systems Explanation:Exploration-based systems can help avoid major costs, including costs related to numerous procedures, steps, and algorithms spread throughout the whole design of modern data management systems.
Q19.
What is the primary goal of an efficient data exploration system?

a.

To ensure complete and correct answers to all queries

b.

To provide a complete representation of all data and value ranges

c.

To engage data analysts in a seamless way and avoid bottlenecks

d.

To process all data in one go to achieve instant results

Discuss
Answer: (c).To engage data analysts in a seamless way and avoid bottlenecks Explanation:The primary goal of an efficient data exploration system is to engage data analysts in a seamless way and avoid being a bottleneck.
Q20.
What does the system need to remember in order to guide the user effectively in data exploration?

a.

All possible queries that the user might pose

b.

The complete and correct results of all user queries

c.

All pixels of the picture being observed

d.

The exact value ranges of all data elements

Discuss
Answer: (c).All pixels of the picture being observed Explanation:The system should remember all pixels of the picture being observed in order to guide the user effectively in data exploration.
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