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IBM Big Data Fundamentals Technical Mastery Test v1 Sample Questions:

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

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

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

A) InfoSphere Streams perform complex analytics on data at rest.
B) 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.
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).

3. What are the ?4 Vs? that characterize IBM?s Big Data initiative?

A) Velocity, Volatility, Variety, Veracity
B) Volume, Volatility, Velocity, Variety
C) Variety, Versions, Velocity, Volatility
D) Veracity, Variety, Volume, Velocity

4. What is HADOOP?

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

Solutions: