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Welcome to the Advanced Data Analytics for Business MCQs Page

Dive deep into the fascinating world of Advanced Data Analytics for Business with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Advanced Data Analytics for Business, a crucial aspect of Big Data Computing. In this section, you will encounter a diverse range of MCQs that cover various aspects of Advanced Data Analytics for Business, 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 Advanced Data Analytics for Business. 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 Advanced Data Analytics for Business. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

Advanced Data Analytics for Business MCQs | Page 7 of 15

Explore more Topics under Big Data Computing

Q61.
What is the primary benefit of Big Data solutions?

a.

Reducing data collection costs

b.

Supporting real-time data processing

c.

Enabling new types of data for analysis

d.

Reducing hardware and software costs

Discuss
Answer: (c).Enabling new types of data for analysis Explanation:Big Data solutions allow organizations to capture new types of data for analysis.
Q62.
What is one of the key advantages of combining Big Data technologies?

a.

Reducing the volume of data in organizations

b.

Simplifying data management and analysis

c.

Supporting real-time data processing

d.

Handling electronic data regardless of volume, variety, or volatility

Discuss
Answer: (d).Handling electronic data regardless of volume, variety, or volatility Explanation:Combining Big Data technologies allows organizations to handle electronic data regardless of volume, variety, or volatility.
Q63.
What is the primary purpose of stream processing systems?

a.

Enhancing data visualization

b.

Analyzing historical data

c.

Filtering and analyzing data in action

d.

Investigating Big Data patterns

Discuss
Answer: (c).Filtering and analyzing data in action Explanation:Stream processing systems are primarily mentioned for filtering and analyzing data in action as it flows through IT systems and across IT networks.
Q64.
What is one of the outcomes of the investigation work done by data scientists using an independent investigative computing platform?

a.

Enhanced data visualization techniques

b.

Creation of new analytic models and results

c.

Adoption of MapReduce

d.

Stream processing of data

Discuss
Answer: (b).Creation of new analytic models and results Explanation:One of the outcomes of the investigation work is the creation of new analytic models and results.
Q65.
What is the MapReduce program composed of?

a.

Multiple functions for data processing

b.

Three main functions for data analysis

c.

Two functions called Map and Reduce

d.

A single function called Analyze

Discuss
Answer: (c).Two functions called Map and Reduce Explanation:The MapReduce program consists of two functions called Map and Reduce.
Q66.
What does the Map function do in a MapReduce program?

a.

It reduces the data volume.

b.

It filters and transforms the input data.

c.

It stores data in partitions.

d.

It schedules tasks on different nodes.

Discuss
Answer: (b).It filters and transforms the input data. Explanation:The Map function reads a set of "records" from an input file, does any desired filtering or transformations, and then outputs a set of intermediate records by processing the input data.
Q67.
How are the output records of the Map function partitioned in MapReduce?

a.

Using a random partitioning technique

b.

Using a hash function

c.

Using a reduce function

d.

Using a split function

Discuss
Answer: (b).Using a hash function Explanation:The output records of the Map function are partitioned using a hash function in MapReduce.
Q68.
What is the primary advantage of using MapReduce for massive data processing?

a.

It requires complex programming skills.

b.

It uses multiple functions for data processing.

c.

It simplifies data partitioning.

d.

It is inspired by concepts of functional languages.

Discuss
Answer: (d).It is inspired by concepts of functional languages. Explanation:One of the primary advantages of using MapReduce for massive data processing is that it is inspired by concepts of functional languages.
Q69.
What is the purpose of the MapReduce scheduler in a distributed processing framework?

a.

It executes the Map and Reduce functions.

b.

It manages data visualization techniques.

c.

It filters and analyzes data in real-time.

d.

It assigns distinct portions of the input file to Map instances.

Discuss
Answer: (d).It assigns distinct portions of the input file to Map instances. Explanation:The MapReduce scheduler assigns distinct portions of the input file to Map instances in a distributed processing framework.
Q70.
How many output files are typically produced by each Map function instance in MapReduce?

a.

One output file per Map function instance

b.

R output files per Map function instance

c.

M output files per Map function instance

d.

M × R output files per Map function instance

Discuss
Answer: (b).R output files per Map function instance Explanation:Each Map function instance typically produces R output files, one for each bucket.
Page 7 of 15

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