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IBM Big Data Fundamentals Technical Mastery Test v1 Sample Questions:

1. Streams jobs can be monitored using the following tools (choose three):

A) Streams universal web management interface.
B) Streamtool command.
C) Streams console.
D) Streams Studio.

2. Which of the following options is NOT CORRECT?

A) Big data solutions are ideal for iterative and exploratory analysis when business measures on data are not predetermined.
B) Big data solutions are ideal for analyzing not only raw structured data, but semi- structured and unstructured data from a wide variety of sources.
C) Big data solutions are ideal for Online Transaction Analytical Process (OLTP) environments.
D) Big data solutions are ideal when all, or most, of the data needs to be analyzed versus a sample of the data; or a sampling of data isn?t nearly as effective as a larger set of data from which to derive analysis.

3. Which of the following options are CORRECT (Choose two)?

A) Users can deploy existing data mining scoring models in Streams applications for real time insights as opposed to running those models on persistent, or stored data.
B) InfoSphere Streams perform complex analytics on data at rest.
C) The Stream Processing Language provides a language that works with the Streams run-time framework to support streaming applications.
D) Users can develop Streams applications using Data Studio Web Console, an Eclipse-based Integrated Development Environment (IDE).

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) 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.
C) 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.
D) Typically, data stored in Hadoop environments is cleaned up before storing in the distributed
file-system.

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