IBM InfoSphere BigInsights Technical Mastery Test v2 - P2090-038 FREE EXAM DUMPS QUESTIONS & ANSWERS

A. Connection via the Pig JDBC driver. B. Connection via the Hive JDBC driver. C. Connection via the Big SQL JDBC driver. D. Connection via the SPL JDBC driver.

A. Big SQL is a feature in Streams that allows for real time analysis of data via standard SQL syntax. B. Big SQL is a feature in BigInsights that allows for native SQL query access for Hadoop, providing full ANSI SQL 92 compliance and standardSQL syntax such as joins, for data contained in a variety of formats such as structured Hive tables, Hbase tables, or csv and other delimitedfiles in HDFS. C. Big SQL is a feature in Data Explorer that allows for indexing of data from SQL sources such as data warehouses. D. Big SQL is a feature in BigInsights that provides a SQL like interface to data contained in Hbase tables only. Other data sources in HDFS mustbe accessed via other means such as HiveQL.

A. You can use the Big SQL IMPORT FROM statement to load data into a HBase table. B. You can use the Big SQL IMPORT FROM statement to load data into a Big SQL table. C. You can use the Big SQL LOAD FROM statement to load data into a Hive table. D. You can use the Big SQL LOAD FROM statement to load data into a Big SQL table.

A. Typically, data stored in Hadoop environments is cleaned up before storing in the distributed file-system. B. 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. 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. 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.