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: Jul 18, 2026     Q & A: 34 Questions and Answers

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IBM 000-N32 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: InfoSphere Streams25%- Integration with other IBM big data solutions
- Architecture and use cases
- Real-time streaming analytics concepts
Topic 2: Big Data Concepts and Characteristics25%- Structured, semi-structured, and unstructured data types
- Business drivers and challenges of big data
- 4 Vs of Big Data: Volume, Velocity, Variety, Veracity
Topic 3: InfoSphere Data Explorer20%- Federated data access and connectivity
- Search and discovery functionality
- Support for diverse data sources
Topic 4: InfoSphere BigInsights and Hadoop Ecosystem30%- Integration with Apache Hadoop
- Architecture and components of InfoSphere BigInsights
- Data storage and processing frameworks
- BigInsights editions and capabilities

IBM Big Data Fundamentals Technical Mastery Test v1 Sample Questions:

1. Which of the following options is NOT CORRECT?

A) Big data solutions are ideal for Online Transaction Analytical Process (OLTP) environments.
B) Big data solutions are ideal for analyzing not only raw structured data, but semi- structured and unstructured data from a wide variety of sources.
C) Big data solutions are ideal for iterative and exploratory analysis when business measures on data are not predetermined.
D) Big data solutions are ideal when all, or most, of the data needs to be analyzed versus a sample of the data; or a sampling of data isn?t nearly as effective as a larger set of data from which to derive analysis.


2. How do enterprises leverage big data platforms?

A) By sitting on top of a large data warehouse solution acting as transparent abstract conversion layer allowing enterprises to query unstructured data.
B) By isolating workloads into a single node, and further processing all the data in sequence.
C) 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.
D) 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.


3. Streams jobs can be monitored using the following tools (choose three):

A) Streamtool command.
B) Streams universal web management interface.
C) Streams console.
D) Streams Studio.


4. What does ?Big Data? represent?

A) Large amounts of unstructured, semi-structured, and structured raw data that cannot be stored, processed or analyzed using traditional relational data warehouses.
B) A database feature capable of converting pre-existing structured data into unstructured raw data.
C) A Hadoop feature capable of processing vast amounts of data in-parallel on large clusters of commodity hardware in a reliable, fault-tolerant manner.
D) Only data stored in the BIGDATA table in any relational database.


Solutions:

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

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