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  • Exam Code: 000-N32
  • Exam Name: IBM Big Data Fundamentals Technical Mastery Test v1
  • Last Updated: Sep 10, 2026
  • Q & A: 34 Questions and Answers
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  • Exam Code: 000-N32
  • Exam Name: IBM Big Data Fundamentals Technical Mastery Test v1
  • Last Updated: Sep 10, 2026
  • Q & A: 34 Questions and Answers
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IBM 000-N32 Exam Syllabus Topics:

SectionObjectives
IBM Big Data Platform- IBM InfoSphere BigInsights overview
- Integration with IBM Information Management products
- IBM InfoSphere Streams overview
Big Data Technologies- NoSQL database fundamentals
- MapReduce concepts
- Hadoop ecosystem fundamentals
Analytics and Business Applications- Real-time analytics scenarios
- Predictive analytics concepts
- Business intelligence and decision support
Big Data Fundamentals- Business value and common use cases
- Big Data challenges and opportunities
- Definition and characteristics of Big Data
Big Data Architecture- Data sources and data ingestion
- Storage and distributed computing concepts
- Data processing and analytics workflow

IBM Big Data Fundamentals Technical Mastery Test v1 Sample Questions:

Question #1

Which of the following tools can be used to configure the InfoSphere Data Explorer environment (choose two) ?

  • A. InfoSphere Data Explorer?s web-based interface
  • B. REST/SOAP APIs
  • C. Data Studio Web Console
  • D. Data Explorer Virtual Desktop
Reveal Solution  Discussion  0

Correct Answer: A,B  🗳️

Question #2

Which of the following components is NOT included in the BigInsights Basic Edition distribution?

  • A. Pig.
  • B. BigSheets.
  • C. Hive.
  • D. Hadoop Distributed File System.
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

Question #3

What is the difference between Hadoop?s MapReduce and IBM?s Adaptive MapReduce feature available in InfoSphere BigInsights?

  • A. Hadoop?s MapReduce is optimized for operating on small partitioned tables stored in the HBase component, while IBM?s Adaptive MapReduce is optimized for operating on large partitioned files.
  • B. Hadoop?s MapReduce is optimized for operating on large files, while IBM?s Adaptive MapReduce is configurable to operate optimized on large or small files or splits.
  • C. Hadoop?s MapReduce is optimized for operating on small files or splits, while IBM?s Adaptive MapReduce is optimized for operating on large partitioned files.
  • D. Hadoop?s MapReduce is optimized for operating on small files or splits, while IBM?s Adaptive MapReduce is optimized for operating on large files stored in individual blocks.
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

Question #4

Which of the following options is CORRECT?

  • A. InfoSphere BigInsights is based on the nonforked core Hadoop distribution, and backwards compatibility with the Apache Hadoop project will always be maintained. Therefore, all applications written for Hadoop will run on BigInsights.
  • B. InfoSphere BigInsights is based on a branched Hadoop distribution, and therefore backwards compatibility is not guaranteed.
  • C. InfoSphere BigInsights is based on the nonforked core Hadoop distribution, but backwards compatibility with the Apache Hadoop project is not guaranteed, therefore applications written for Hadoop might not run on BigInsights.
  • D. InfoSphere BigInsights is a distributed file system used as base for Hadoop distributions.
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

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