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IBM Big Data Fundamentals Technical Mastery Test v1 Sample Questions:

1. What does ?Big Data? represent?

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

2. Which of the following components is a feature from InfoSphere Data Explorer's Discovery module?

A) Auto-commit
B) Auto-correction
C) Auto-save
D) Auto-classification

3. 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.

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) 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.
C) 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.
D) 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.

Solutions: