IBM 000-N32 : IBM Big Data Fundamentals Technical Mastery Test v1
- Exam Code: 000-N32
- Exam Name: IBM Big Data Fundamentals Technical Mastery Test v1
- Updated: Oct 13, 2026
- Q & A: 34 Questions and Answers
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IBM 000-N32 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Big Data Architecture | - Data ingestion and processing pipelines - Distributed computing concepts |
| Topic 2: Big Data Technologies | - MapReduce and distributed processing - Hadoop ecosystem overview - Spark fundamentals |
| Topic 3: Big Data Analytics | - Data processing and analytics techniques - Use cases and business applications |
| Topic 4: Big Data Concepts | - 3Vs / 5Vs of big data (volume, velocity, variety, etc.) - Definition and characteristics of big data |
| Topic 5: Data Storage and Management | - NoSQL databases - HDFS and distributed storage systems |
IBM Big Data Fundamentals Technical Mastery Test v1 Sample Questions:
The following types of indexes are available in the InfoSphere BigInsights? Large Scale indexing feature, EXCEPT:
- A. MapReduce index
- B. Partitioned index
- C. Parallel index
- D. Real-time index
Correct Answer: A 🗳️
Which of the following options is CORRECT regarding InfoSphere Data Explorer?s annotators?
- A. InfoSphere Data Explorer?s annotators allow users to interact with search results by providing
feedback about the result's value, and by
adding useful information and communication with other users. - B. InfoSphere Data Explorer?s annotators allow users to save results in a private/public folder for
later review or sharing. - C. InfoSphere Data Explorer?s annotators allow users to create groups of search results.
- D. InfoSphere Data Explorer?s annotators is an add-on feature capable of handling of a variety of
data formats and types, including structured,
semi-structured and unstructured, as well as the special demands of rich media and transactional
data.
Correct Answer: A 🗳️
How do enterprises leverage big data platforms?
- A. By isolating workloads into a single node, and further processing all the data in sequence.
- B. By modifying the data being streamed using pre-existing ETL transformations, and storing the final formatted data into a data warehouse for further enterprise analysis.
- C. By sitting on top of a large data warehouse solution acting as transparent abstract conversion layer allowing enterprises to query unstructured data.
- D. By storing all of the data in its native business object format, so the enterprise can get value out of it through massive parallelism using readily available components.
Correct Answer: D 🗳️
What is HADOOP?
- A. Hadoop is a universal Big Data programming language used to query large datasets.
- B. Hadoop is framework capable of transforming raw, unstructured data into plain, regular data readable by traditional data warehouses.
- C. Hadoop is a framework that allows for the distributed processing of large data sets across clusters of computers using a simple programming model.
- D. Hadoop is a single-node file system used as a base for storing traditional formatted data.
Correct Answer: C 🗳️
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