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IBM Big Data Fundamentals Technical Mastery Test v1 Sample Questions:

1. Which of the following tools can be used to configure the InfoSphere Data Explorer environment (choose two) ?

A) Data Studio Web Console
B) InfoSphere Data Explorer?s web-based interface
C) Data Explorer Virtual Desktop
D) REST/SOAP APIs

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

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

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

A) InfoSphere Streams is a powerful analytic computing platform capable of analyzing data in real time with micro-latency.
B) 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.
C) InfoSphere Streams is a powerful analytic computing platform capable of gathering large quantities of data, manipulating the data, and storing it on disk.
D) 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.

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 data warehousing environments is rarely filtered and pre-processed.
On the other hand, data injected into Hadoop
environments is always pre-processed and filtered.
B) Typically, data stored in Hadoop environments is cleaned up before storing in the distributed
file-system.
C) 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.
D) 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.

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