P2090-038 IBM InfoSphere BigInsights Technical Mastery Test v2 Questions and Answers

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.

The Text Analytics component only extracts information from structured data stored in a relational database.

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.

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.

Hadoop Map Reduce is optimized for operating on small files or splits, while IBM Adaptive MapReduce is optimized for operating on largepartitioned files.

Hadoop MapReduce is optimized for operating on large files, while IBM Adaptive MapReduce is configurable to operate optimized on large or small files or splits

Hadoop MapReduce is optimized for operating on small files or splits, while IBM Adaptive MapReduce is optimized for operating on large files stored in individual blocks.

Hadoop MapReduce is optimized for operating on small partitioned tables stored in the HBase component, while IBM? Adaptive MapReduceis optimized for operating on large partitioned files.

The data is divided into blocks, and copies of these blocks are replicated across multiple servers in the Hadoop cluster.

The data converted into a single block, and the block is stored in just one of the servers in the Hadoop cluster.

The data is divided into blocks, each block is stored in a different server in the Hadoop cluster, but the blocks are not replicated.

The data is converted into a single block, and copies of this block are replicated across multiple servers in the Hadoop cluster.

Applications will connect using custom made connectors programmed in SPL.

Applications will connect using standard JDBC and ODBC drivers that come with InfoSphere BigInsights.

Applications will connect using the JAQL programming language.

Applications will connect using either HiveQL or Pig programming languages.

There is no direct interaction between InfoSphere BigInsighs and data warehousing environments. However, InfoSphere Streams can be used to stream data between the two environments.

Frequently accessed data should be maintained in the BigInsights environment while old?or outdated information can be offloaded to the Frequently accessed data should be maintained in the BigInsights environment while ?old?or outdated information can be offloaded to the warehouse environment.

InfoSphere BigInsights Enterprise Edition also comes with a standard Java Database Connectivity (JDBC) connector, making it possible for organizations to quickly integrate with a wide variety of data and information systems, including Oracle, Microsoft SQL Server, MySQL and Teradata.

There is no integration between InfoSphere BigInsights and warehousing environments since they deal with different type of data.

Text Analytics.

Adaptive MapReduce.

General Parallel File System.

BigSheets.