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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

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Answer: (c).Enabling new types of data for analysis Explanation:Big Data solutions allow organizations to capture new types of data for analysis.
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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.
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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?
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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.
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Answer: (c).Two functions called Map and Reduce Explanation:The MapReduce program consists of two functions called Map and Reduce.
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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?
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Answer: (b).Using a hash function Explanation:The output records of the Map function are partitioned using a hash function in MapReduce.
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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.
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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.
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Answer: (b).R output files per Map function instance Explanation:Each Map function instance typically produces R output files, one for each bucket.

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