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IBM P2090-038 Exam Syllabus Topics:

IBM InfoSphere BigInsights Technical Mastery Test v2 Sample Questions:

1. Which of the following options best describes the proper usage of MapReduce jobs in Hadoop environments?

A) MapReduce jobs are used to process small amounts of data in-parallel on expensive hardware, without fault-tolerance.
B) MapReduce jobs are used to execute sequential search outside the Hadoop environment using a built-in UDF to access information stored in non-relational databases.
C) MapReduce jobs are used to process structured data in sequence, with fault-tolerance.
D) MapReduce jobs are used to process vast amounts of data in-parallel on large clusters of commodity hardware in a reliable, fault-tolerant manner.

2. Which of the following InfoSphere Biglnsights editions includes the Adaptive MapReduce feature?

A) InfoSphere Biglnsights Extended Developer Edition.
B) InfoSphere Biglnsights Advanced Enterprise Edition.
C) InfoSphere Biglnsights Express Edition.
D) InfoSphere Biglnsights Enterprise Edition.

3. Which of the following integrated development environment (IDE) can be used to develop programs to be used with InfoSphere BigInsights?

A) Eclipse with InfoSphere BigInsights plug-in.
B) InfoSphere Data Explorer.
C) IBM Data Studio with InfoSphere Data Explorer plug-in.
D) InfoSphere Streams Studio

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

A) 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.
B) 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.
C) The Text Analytics component only extracts information from structured data stored in a relational database.
D) 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.

Solutions: