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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 6 of 15

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Q51.
What is multivariate statistical analysis primarily grounded in?

a.

Artificial intelligence

b.

Database technologies

c.

Statistical theories and models

d.

Heuristic search

Discuss
Answer: (c).Statistical theories and models Explanation:Multivariate statistical analysis is primarily grounded in statistical theories and models.
Q52.
Which community contributed to the development of optimization techniques and heuristic search for business analytics?

a.

Artificial intelligence researchers

b.

Database communities

c.

Management science community

d.

Data mining community

Discuss
Answer: (c).Management science community Explanation:Optimization techniques and heuristic search were developed in the management science community.
Q53.
What is the focus of privacy preserving data mining?

a.

Improving data accuracy

b.

Anonymization techniques

c.

Enhancing data visualization

d.

Web crawling techniques

Discuss
Answer: (b).Anonymization techniques Explanation:Privacy preserving data mining focuses on various anonymization techniques.
Q54.
What is the key factor that has made process mining possible?

a.

Availability of event logs

b.

Advances in machine learning

c.

Use of Bayesian networks

d.

Adoption of Big Data technologies

Discuss
Answer: (a).Availability of event logs Explanation:Process mining has become possible due to the availability of event logs in various businesses.
Q55.
What is the main area of application for process mining?

a.

Finance and accounting

b.

Healthcare and supply chains

c.

Retail and marketing

d.

Social media analysis

Discuss
Answer: (b).Healthcare and supply chains Explanation:Process mining has been applied in areas such as healthcare and supply chains.
Q56.
What distinguishes semistructured data from structured data?

a.

Structured data can be processed using MapReduce.

b.

Semistructured data requires ad hoc and one-time processing.

c.

Structured data is typically unstructured text.

d.

Semistructured data is handled by RDBMS.

Discuss
Answer: (b).Semistructured data requires ad hoc and one-time processing. Explanation:Semistructured data may call for ad hoc and one-time extraction, parsing, processing, indexing, and analytics.
Q57.
Which technology has been hailed as a revolutionary platform for large-scale, massively parallel data access?

a.

Apache Hadoop

b.

Mahout

c.

MapReduce

d.

Hive

Discuss
Answer: (c).MapReduce Explanation:MapReduce has been hailed as a revolutionary platform for large-scale, massively parallel data access.
Q58.
What is the primary advantage of analytic relational systems?

a.

Optimized for structured data only

b.

Optimized for data collection

c.

Optimized for complex analytic processing

d.

Optimized for non-relational data

Discuss
Answer: (c).Optimized for complex analytic processing Explanation:Analytic relational systems are optimized for supporting complex analytic processing against both structured and multistructured data.
Q59.
What role does non-relational systems play in Big Data management?

a.

Efficient query processing

b.

Handling graph data

c.

Supporting structured data only

d.

Enabling data summarization

Discuss
Answer: (b).Handling graph data Explanation:Non-relational systems are well suited to the processing of large amounts of multistructured data, including handling complex data such as graph data.
Q60.
What types of data are analytic relational systems evolving to support?

a.

Only relational data

b.

Structured and multistructured data

c.

Only unstructured text

d.

Non-relational data

Discuss
Answer: (b).Structured and multistructured data Explanation:Analytic relational systems are evolving to support not only relational data but also other types of data structures, including structured and multistructured data.
Page 6 of 15

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