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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 14 of 15

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Q131.
What is the primary focus of customer analytics in CRM BPO?

a.

Managing customer relationships

b.

Handling structured data only

c.

Capturing unstructured data

d.

Analyzing employee performance

Discuss
Answer: (c).Capturing unstructured data Explanation:Customer analytics in CRM BPO focuses on capturing both structured and unstructured data.
Q132.
What is one of the main challenges addressed in customer analytics?

a.

Data linking

b.

Document clustering

c.

Text annotation

d.

Concept discovery

Discuss
Answer: (d).Concept discovery Explanation:Concept discovery is one of the main challenges addressed in customer analytics.
Q133.
How does customer analytics handle concept expansion?

a.

By using word clustering algorithms

b.

By maintaining an ontology of concepts

c.

By relying on predictive modeling

d.

By performing data linking

Discuss
Answer: (b).By maintaining an ontology of concepts Explanation:Customer analytics handles concept expansion by maintaining an ontology of concepts and suggesting synonyms.
Q134.
Why is unstructured data considered valuable in generating business insights?

a.

It is easy to manage and process

b.

It provides rich and valuable information

c.

It requires less effort from human data miners

d.

It is less noisy compared to structured data

Discuss
Answer: (b).It provides rich and valuable information Explanation:Unstructured data is considered valuable because it provides rich and valuable information for generating business insights.
Q135.
What role does the SentimentMiner tool play in customer analytics?

a.

It performs data linking

b.

It identifies key drivers of customer sentiments

c.

It suggests synonyms for concepts

d.

It segregates concepts based on sentiment

Discuss
Answer: (d).It segregates concepts based on sentiment Explanation:The SentimentMiner tool segregates concepts based on sentiment in customer analytics.
Q136.
What does customer analytics aim to provide to business analysts?

a.

Data linking capabilities

b.

Text clustering algorithms

c.

Actionable business insights

d.

Sentiment mining tools

Discuss
Answer: (c).Actionable business insights Explanation:Customer analytics aims to provide business analysts with actionable business insights.
Q137.
What is the main challenge enterprises face regarding data?

a.

Managing historical data

b.

Accumulating massive amounts of data

c.

Predictive modeling

d.

Data scalability

Discuss
Answer: (b).Accumulating massive amounts of data Explanation:Enterprises face the challenge of accumulating massive amounts of data.
Q138.
Which technology is IBM Infosphere BigInsights based on for scalability?

a.

Apache Hadoop

b.

Apache Spark

c.

IBM Watson

d.

IBM Db2

Discuss
Answer: (a).Apache Hadoop Explanation:IBM Infosphere BigInsights relies on Apache Hadoop for scalability.
Q139.
What kind of data does IBM Infosphere Streams process in real-time?

a.

Structured data

b.

Historical data

c.

Streaming data

d.

Predictive data

Discuss
Answer: (c).Streaming data Explanation:IBM Infosphere Streams processes streaming data in real-time.
Q140.
How can a telecommunications company benefit from using both BigInsights and Streams?

a.

By analyzing historical data in real-time

b.

By generating promotions based on streaming call records

c.

By using predictive models to analyze historical data

d.

By reducing the need for analytics platforms

Discuss
Answer: (b).By generating promotions based on streaming call records Explanation:A telecommunications company can benefit by generating promotions in real-time based on streaming call records while analyzing historical data.
Page 14 of 15

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