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IBM Big Data Fundamentals Technical Mastery Test v1 Sample Questions:

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

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

2. Which of the following options is NOT CORRECT?

A) Big data solutions are ideal for analyzing not only raw structured data, but semi- structured and unstructured data from a wide variety of sources.
B) 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.
C) Big data solutions are ideal for Online Transaction Analytical Process (OLTP) environments.
D) Big data solutions are ideal for iterative and exploratory analysis when business measures on data are not predetermined.

3. What is good fit for Hadoop Distributed File System (HDFS)?

A) Applications requiring low latency data access.
B) Multiple writers accessing the same file.
C) Applications requiring high throughput of data.
D) Lots of small files.

4. What is HADOOP?

A) Hadoop is a single-node file system used as a base for storing traditional formatted data.
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 universal Big Data programming language used to query large datasets.
D) Hadoop is framework capable of transforming raw, unstructured data into plain, regular data readable by traditional data warehouses.

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