IBM 000-N32 Q&A - in .pdf

  • 000-N32 pdf
  • Exam Code: 000-N32
  • Exam Name: IBM Big Data Fundamentals Technical Mastery Test v1
  • Updated: Sep 07, 2026
  • Q & A: 34 Questions and Answers
  • Convenient, easy to study.
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  • Exam Code: 000-N32
  • Exam Name: IBM Big Data Fundamentals Technical Mastery Test v1
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  • Updated: Sep 07, 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
  • Updated: Sep 07, 2026
  • Q & A: 34 Questions and Answers
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IBM 000-N32 Exam Syllabus Topics:

SectionWeightObjectives
IBM InfoSphere BigInsights35%- Architecture and components
  • 1. Administration tools
    • 2. Text Analytics
      • 3. BigSheets
        - Security and authentication
        - Data processing and storage
        IBM InfoSphere Streams20%- Real-time data processing
        - Architecture and development tools
        - Stream computing concepts
        Big Data Concepts & Architecture30%- Characteristics of Big Data (4 Vs)
        - Hadoop ecosystem fundamentals
        • 1. MapReduce
          • 2. HDFS
            • 3. YARN
              - Big Data use cases and business value
              IBM Big Data Portfolio & Solutions15%- Comparison with competing solutions
              - Integration and deployment scenarios
              - Overview of IBM Big Data offerings

              IBM Big Data Fundamentals Technical Mastery Test v1 Sample Questions:

              Question 1

              Which of the following components is a feature from InfoSphere Data Explorer's Discovery module?

              A. Auto-classification
              B. Auto-save
              C. Auto-commit
              D. Auto-correction


              Question 2

              What is good fit for Hadoop Distributed File System (HDFS)?

              A. Applications requiring high throughput of data.
              B. Lots of small files.
              C. Multiple writers accessing the same file.
              D. Applications requiring low latency data access.


              Question 3

              The following types of indexes are available in the InfoSphere BigInsights? Large Scale indexing feature, EXCEPT:

              A. MapReduce index
              B. Partitioned index
              C. Real-time index
              D. Parallel index


              Question 4

              Which of the following options are CORRECT (Choose two)?

              A. Users can deploy existing data mining scoring models in Streams applications for real time insights as opposed to running those models on persistent, or stored data.
              B. Users can develop Streams applications using Data Studio Web Console, an Eclipse-based Integrated Development Environment (IDE).
              C. The Stream Processing Language provides a language that works with the Streams run-time framework to support streaming applications.
              D. InfoSphere Streams perform complex analytics on data at rest.


              Solutions:

              Question 1
              Answer: A
              Question 2
              Answer: A
              Question 3
              Answer: A
              Question 4
              Answer: A,C

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