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IBM 000-N38 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Security and Administration | - Cluster monitoring and maintenance - User authentication and authorization |
| Topic 2: Big Data and Hadoop Fundamentals | - Hadoop ecosystem components - HDFS architecture and data storage principles |
| Topic 3: Data Processing and Analytics | - Text analytics and advanced analytics capabilities - Big SQL and query processing - MapReduce processing model |
| Topic 4: Data Ingestion and Integration | - Integration with external data sources - Data loading techniques |
| Topic 5: IBM InfoSphere BigInsights Architecture | - BigInsights system components and deployment models - Cluster configuration and management |
IBM InfoSphere BigInsights Technical Mastery Test v2 Sample Questions:
1. What is the difference between Hadoop MapReduce and IBM Adaptive MapReduce feature available in InfoSphere BigInsights?
A) 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
B) 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.
C) 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.
D) Hadoop Map Reduce is optimized for operating on small files or splits, while IBM Adaptive MapReduce is optimized for operating on largepartitioned files.
2. What is Hadoop?
A) Hadoop is a single-node file system used as a base for storing traditional formatted data.
B) Hadoop is a framework that allows for the distributed processing of large data sets across clusters of computers using a simple programming model.
C) Hadoop is a universal Big Data programming language used to query large datasets.
D) Hadoop is programming language capable of transforming raw, unstructured data into plain, regular data readable by traditional data warehouses.
3. 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) Text Analytics.
C) BigSheets.
D) Adaptive MapReduce.
4. InfoSphere BigInsights offers the following benefits to your organization, EXCEPT:
A) It cuts costs by providing an efficient compression algorithm based on row level compression using a dictionary to store repetitive patterns.
B) It enables analysis at scale.
C) It complements your existing infrastructure by extending your data collection and analysis capabilities.
D) It integrates data from a variety of structured and unstructured sources.
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: B | Question # 3 Answer: B | Question # 4 Answer: A |
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