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IBM Big Data Fundamentals Technical Mastery Test v1 Sample Questions:

1. Which of the following options contain security enhancements available in InfoSphere BigInsights (Choose two) ?

A) Trusted Context.
B) Kerberos authentication protocol.
C) LDAP authentication
D) Secure file transfers through SFTP protocol.

2. 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 partitioned files.
B) 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.
C) 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.
D) 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.

3. Which of the following options is CORRECT?

A) InfoSphere BigInsights is based on the nonforked core Hadoop distribution, and backwards compatibility with the Apache Hadoop project will always be maintained. Therefore, all applications written for Hadoop will run on BigInsights.
B) InfoSphere BigInsights is based on a branched Hadoop distribution, and therefore backwards compatibility is not guaranteed.
C) InfoSphere BigInsights is a distributed file system used as base for Hadoop distributions.
D) InfoSphere BigInsights is based on the nonforked core Hadoop distribution, but backwards compatibility with the Apache Hadoop project is not guaranteed, therefore applications written for Hadoop might not run on BigInsights.

4. Which of the following options best describes the differences between a traditional data warehouse environment and a Hadoop environment?

A) Typically, data stored in Hadoop environments is cleaned up before storing in the distributed
file-system.
B) Traditional data warehousing environments are mostly ideal for analyzing structured data from
various systems, while a Hadoop environment is
well suited to deal with semi-structured and unstructured data, as well as when a data discovery
process is needed.
C) Typically, data stored in data warehousing environments is rarely filtered and pre-processed.
On the other hand, data injected into Hadoop
environments is always pre-processed and filtered.
D) Hadoop environments are mostly ideal for analyzing structured and semi-structured data from a
single system, while traditional data
warehousing environment is well suited to deal with unstructured data, as well as when a data
discovery process is needed.

Solutions: