IBM P2090-032 Questions & Answers - in .pdf
- Total Q&A: 34
- Update: May 27, 2026
- Price: $49.99
- Vendor: IBM
- Exam Code: P2090-032
- Exam Name: IBM Big Data Fundamentals Technical Mastery Test v1
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IBM P2090-032 Q&A - Testing Engine
- Total Q&A: 34
- Update: May 27, 2026
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- Vendor: IBM
- Exam Code: P2090-032
- Exam Name: IBM Big Data Fundamentals Technical Mastery Test v1
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IBM Big Data Fundamentals Technical Mastery Test v1 Sample Questions:
1. In a traditional Hadoop stack, which of the following components provides data warehouse infrastructure and allows SQL developers and business analysts to leverage their existing SQL skills?
A) Hive.
B) Avro.
C) Text analytics.
D) Zookeeper.
2. Which of the following options is CORRECT regarding InfoSphere Data Explorer?s annotators?
A) 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.
B) InfoSphere Data Explorer?s annotators allow users to create groups of search results.
C) InfoSphere Data Explorer?s annotators allow users to save results in a private/public folder for
later review or sharing.
D) 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.
3. Which of the following options contain security enhancements available in InfoSphere BigInsights (Choose two) ?
A) Trusted Context.
B) Secure file transfers through SFTP protocol.
C) LDAP authentication
D) Kerberos authentication protocol.
4. What is the difference between Hadoop?s MapReduce and IBM?s Adaptive MapReduce feature available in InfoSphere BigInsights?
A) Hadoop?s MapReduce is optimized for operating on small files or splits, while IBM?s Adaptive MapReduce is optimized for operating on large files stored in individual blocks.
B) Hadoop?s MapReduce is optimized for operating on large files, while IBM?s Adaptive MapReduce is configurable to operate optimized on large or small files or splits.
C) Hadoop?s MapReduce is optimized for operating on small files or splits, while IBM?s Adaptive MapReduce is optimized for operating on large partitioned files.
D) Hadoop?s MapReduce is optimized for operating on small partitioned tables stored in the HBase component, while IBM?s Adaptive MapReduce is optimized for operating on large partitioned files.
Solutions:
Question # 1 Answer: A | Question # 2 Answer: D | Question # 3 Answer: B,C | Question # 4 Answer: B |
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