IBM P2090-032 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Big Data Fundamentals | - Big Data challenges and opportunities - Definition and characteristics of Big Data - Business value and common use cases |
| Topic 2: Big Data Architecture | - Storage and distributed computing concepts - Data sources and data ingestion - Data processing and analytics workflow |
| Topic 3: Analytics and Business Applications | - Predictive analytics concepts - Real-time analytics scenarios - Business intelligence and decision support |
| Topic 4: IBM Big Data Platform | - IBM InfoSphere Streams overview - Integration with IBM Information Management products - IBM InfoSphere BigInsights overview |
| Topic 5: Big Data Technologies | - Hadoop ecosystem fundamentals - NoSQL database fundamentals - MapReduce concepts |
IBM Big Data Fundamentals Technical Mastery Test v1 Sample Questions:
1. Which of the following statements is NOT CORRECT?
A) InfoSphere Streams supports communications to Internet Protocol version 6 (IPv6) networks.
B) InfoSphere Streams jobs must be coded using either HiveQL or Jaql languages.
C) InfoSphere Streams provides support for reuse of existing Java or C++ code, as well as Predictive Model Markup Language (PMML) models.
D) InfoSphere Streams supports both command line and graphical interfaces to administer the
2. Which of the following InfoSphere BigInsights features provides a vast library of extractors enabling actionable insights from large amounts of native textual data?
A) General Parallel File System.
B) Adaptive MapReduce.
C) BigSheets.
D) Text Analytics.
3. How do big data solutions interact with the existing enterprise infrastructure?
A) Big data solutions must substitute for the existing enterprise infrastructure; therefore there is no interaction between them.
B) Big data solutions works in parallel with the existing enterprise infrastructure leveraging all the unstructured raw data that cannot be processed and stored in a traditional data warehouse solutions.
C) Big data solutions are placed on top of the existing enterprise infrastructure, acting as a transparent layer converting unstructured raw data into structured, readable data, and storing the final results in a traditional data warehouse.
D) Big data solutions must be isolated into a separate virtualized environment optimized for sequential workloads, so that it doesn?t interact with existing infrastructure.
4. How is data stored in a Hadoop cluster?
A) The data converted into a single block, and the block is stored in just one of the servers in the Hadoop cluster.
B) The data is converted into a single block, and copies of this block are replicated across multiple servers in the Hadoop cluster.
C) The data is divided into blocks, each block is stored in a different server in the Hadoop cluster, but the blocks are not replicated.
D) The data is divided into blocks, and copies of these blocks are replicated across multiple servers in the Hadoop cluster.
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: D | Question # 3 Answer: B | Question # 4 Answer: D |
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