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IBM Big Data Fundamentals Technical Mastery Test v1 Sample Questions:

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

A) IBM InfoSphere Streams Studio improves performance and cuts costs by providing expert
advice on writing high quality queries and improving
database design.
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 provides an integrated, modular environment for database
development and administration of DB2 databases,
Informix, and other non-IBM databases.

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

A) 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.
B) 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.
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.

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

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

4. How do big data solutions interact with the existing enterprise infrastructure?

A) Big data solutions are placed on top of the existing enterprise infrastructure, acting as a transparent layer converting unstructured raw data into structured, readable data, and storing the final results in a traditional data warehouse.
B) Big data solutions works in parallel with the existing enterprise infrastructure leveraging all the unstructured raw data that cannot be processed and stored in a traditional data warehouse solutions.
C) Big data solutions must substitute for the existing enterprise infrastructure; therefore there is no interaction between them.
D) Big data solutions must be isolated into a separate virtualized environment optimized for sequential workloads, so that it doesn?t interact with existing infrastructure.

Solutions: