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IBM InfoSphere BigInsights Technical Mastery Test v2 Sample Questions:

1. Which of the following options is CORRECT?

A) InfoSphere BigInsights is a distributed file system used as base for Hadoop distributions.
B) InfoSphere BigInsights is based on the non forked core Hadoop distribution, and backwards compatibility with the Apache Hadoop project will always be maintained. Therefore, all applications written for Hadoop will run on BigInsights.
C) InfoSphere BigInsights is based on a branched Hadoop distribution, and therefore backwards compatibility is not guaranteed.
D) InfoSphere BigInsights is based on the non forked core Hadoop distribution, but backwards compatibility with the Apache Hadoop project is not guaranteed, therefore applications written for Hadoop might not run on BigInsights.

2. Which of the following options is CORRECT in regards of Text Analytics component?

A) The Text Analytics component is a programming model for processing large data sets, and the name of an implementation of the model by Google. Text Analytics is typically used to do distributed computing on clusters of computers.
B) Jaql is the language for developing text analytics extractors in the InfoSphere BigInsights Text Analytics system. A Jaql extractor is a program written in Jaql that extracts structured information from unstructured or semi-structured text.
C) The Text Analytics component extracts information from unstructured and semi-structured data. By using its components, enterprises can analyze large volumes of text and produce annotated documents that provide valuable insights into unconventionally stored data.
D) The Text Analytics component only extracts information from structured data stored in a relational database.

3. Which of the following options DOES NOT describe an advantage of InfoSphere BigInsights on top of regular standalone Hadoop distributions?

A) Support to HiveQL and PigLatin languages.
B) Integrated install
C) Adaptive MapReduce
D) BigSheets

4. Which of the following options best describes the differences between a traditional data warehouse environment and a Hadoop environment?

A) Traditional data warehousing environments are mostly ideal for analyzing structured data from various systems, while a Hadoop environment is well suited to deal with structured, semi-structured, and unstructured data, as well as when a data discovery process is needed.
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) 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.
D) Typically, data stored in Hadoop environments is cleaned up before storing in the distributed file-system.

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