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IBM 000-N32 exam : IBM Big Data Fundamentals Technical Mastery Test v1

000-N32 Exam Simulator
  • Exam Code: 000-N32
  • Exam Name: IBM Big Data Fundamentals Technical Mastery Test v1
  • Updated: May 31, 2026
  • Q & A: 34 Questions and Answers
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IBM Big Data Fundamentals Technical Mastery Test v1 Sample Questions:

1. In regards of InfoSphere Streams, Which of the following options is CORRECT?

A) InfoSphere Streams is a powerful analytic computing platform capable of gathering large quantities of data, manipulating the data, and storing it on disk.
B) InfoSphere Streams is a powerful analytic computing platform capable of analyzing data in real time with micro-latency.
C) InfoSphere Streams is web administration graphical user interface (GUI) capable of setting up a secure communication channel to stream post-processed data from a Hadoop cluster into a relational database, such as IBM DB2.
D) InfoSphere Streams is an extract, transform, and load (ETL) platform that is capable of integrating small volumes of data across a wide variety of data sources and target applications.


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

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


3. Which of the following options best describes the proper usage of MapReduce jobs in Hadoop environments?

A) MapReduce jobs are used to process structured data in sequence, with fault-tolerance.
B) MapReduce jobs are used to execute sequential search outside the Hadoop environment using a built-in UDF to access information stored in non-relational databases.
C) MapReduce jobs are used to process small amounts of data in-parallel on expensive hardware, without fault-tolerance.
D) MapReduce jobs are used to process vast amounts of data in-parallel on large clusters of commodity hardware in a reliable, fault-tolerant manner.


4. How do big data solutions interact with the existing enterprise infrastructure?

A) Big data solutions works in parallel with the existing enterprise infrastructure leveraging all the unstructured raw data that cannot be processed and stored in a traditional data warehouse solutions.
B) Big data solutions are placed on top of the existing enterprise infrastructure, acting as a transparent layer converting unstructured raw data into structured, readable data, and storing the final results in a traditional data warehouse.
C) Big data solutions must be isolated into a separate virtualized environment optimized for sequential workloads, so that it doesn?t interact with existing infrastructure.
D) Big data solutions must substitute for the existing enterprise infrastructure; therefore there is no interaction between them.


Solutions:

Question # 1
Answer: B
Question # 2
Answer: D
Question # 3
Answer: D
Question # 4
Answer: A

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