IBM P2090-032 valid exam dumps : IBM Big Data Fundamentals Technical Mastery Test v1

  • Exam Code: P2090-032
  • Exam Name: IBM Big Data Fundamentals Technical Mastery Test v1
  • Updated: Aug 04, 2026
  • Q&As: 34 Questions and Answers

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IBM P2090-032 Exam Syllabus Topics:

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

IBM Big Data Fundamentals Technical Mastery Test v1 Sample Questions:

1. Which of the following options is CORRECT?

A) InfoSphere Data Explorer is not able to mirror pre-existing security frameworks, therefore it doesn?t make use of industry-standard authentication and authorization processes already in place.
B) InfoSphere Data Explorer provides powerful navigation capabilities across all the important information stored exclusively into Hadoop Distributed File System in a single view. No other file systems are supported.
C) InfoSphere Data Explorer uses a vector-based index for unique search and indexing flexibility.
D) InfoSphere Data Explorer can find, extract and deliver content regardless of format or where it resides.


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

A) Big data solutions must substitute for the existing enterprise infrastructure; therefore there is no interaction between them.
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 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.


3. What does ?Big Data? represent?

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


4. 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.


Solutions:

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

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