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IBM 000-N32 Exam Syllabus Topics:

IBM Big Data Fundamentals Technical Mastery Test v1 Sample Questions:

Question 1

What is HADOOP?

A. Hadoop is a framework that allows for the distributed processing of large data sets across clusters of computers using a simple programming model.
B. Hadoop is framework capable of transforming raw, unstructured data into plain, regular data readable by traditional data warehouses.
C. Hadoop is a universal Big Data programming language used to query large datasets.
D. Hadoop is a single-node file system used as a base for storing traditional formatted data.

Question 2

What is the purpose of IBM InfoSphere Streams Studio?

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

Question 3

How is data stored in a Hadoop cluster?

A. The data is divided into blocks, each block is stored in a different server in the Hadoop cluster, but the blocks are not replicated.
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, and copies of these blocks are replicated across multiple servers in the Hadoop cluster.

Question 4

What does ?Big Data? represent?

A. A database feature capable of converting pre-existing structured data into unstructured raw data.
B. A Hadoop feature capable of processing vast amounts of data in-parallel on large clusters of commodity hardware in a reliable, fault-tolerant manner.
C. Large amounts of unstructured, semi-structured, and structured raw data that cannot be stored, processed or analyzed using traditional relational data warehouses.
D. Only data stored in the BIGDATA table in any relational database.

Solutions: