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IBM Big Data Fundamentals Technical Mastery Test v1 Sample Questions:

1. How is data stored in a Hadoop cluster?

A) The data is divided into blocks, and copies of these blocks are replicated across multiple servers in the Hadoop cluster.
B) The data converted into a single block, and the block is stored in just one of the servers in the Hadoop cluster.
C) The data is converted into a single block, and copies of this block are replicated across multiple servers in the Hadoop cluster.
D) The data is divided into blocks, each block is stored in a different server in the Hadoop cluster, but the blocks are not replicated.

2. What is the purpose of IBM InfoSphere Streams Studio?

A) IBM InfoSphere Streams Studio is an Eclipse-ready tool that enables you to create, edit,
visualize, test, debug, and run MapReduce jobs for
virtualized applications.
B) IBM InfoSphere Streams Studio is an Eclipse-ready tool that enables you to create, edit,
visualize, test, debug, and run Streams Processing
Language (SPL) and SPL mixed-mode applications.
C) IBM InfoSphere Streams Studio provides an integrated, modular environment for database
development and administration of DB2 databases,
Informix, and other non-IBM databases.
D) IBM InfoSphere Streams Studio improves performance and cuts costs by providing expert
advice on writing high quality queries and improving
database design.

3. How do enterprises leverage big data platforms?

A) By isolating workloads into a single node, and further processing all the data in sequence.
B) By modifying the data being streamed using pre-existing ETL transformations, and storing the final formatted data into a data warehouse for further enterprise analysis.
C) By sitting on top of a large data warehouse solution acting as transparent abstract conversion layer allowing enterprises to query unstructured data.
D) By storing all of the data in its native business object format, so the enterprise can get value out of it through massive parallelism using readily available components.

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) 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.
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.