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IBM P2090-032 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| InfoSphere Data Explorer | 20% | - Federated data access and connectivity - Search and discovery functionality - Support for diverse data sources |
| Big Data Concepts and Characteristics | 25% | - 4 Vs of Big Data: Volume, Velocity, Variety, Veracity - Structured, semi-structured, and unstructured data types - Business drivers and challenges of big data |
| InfoSphere Streams | 25% | - Real-time streaming analytics concepts - Integration with other IBM big data solutions - Architecture and use cases |
| InfoSphere BigInsights and Hadoop Ecosystem | 30% | - Data storage and processing frameworks - Architecture and components of InfoSphere BigInsights - BigInsights editions and capabilities - Integration with Apache Hadoop |
IBM Big Data Fundamentals Technical Mastery Test v1 Sample Questions:
1. In regards of InfoSphere Streams, Which of the following options is CORRECT?
A) InfoSphere Streams is an extract, transform, and load (ETL) platform that is capable of integrating small volumes of data across a wide variety of data sources and target applications.
B) InfoSphere Streams is a powerful analytic computing platform capable of gathering large quantities of data, manipulating the data, and storing it on disk.
C) InfoSphere Streams is web administration graphical user interface (GUI) capable of setting up a secure communication channel to stream post-processed data from a Hadoop cluster into a relational database, such as IBM DB2.
D) InfoSphere Streams is a powerful analytic computing platform capable of analyzing data in real time with micro-latency.
2. InfoSphere Data Explorer accommodates data variety through (choose three):
A) Federated connectivity in the cloud and on-premise.
B) Broad connectivity to a wide range of data management systems and applications.
C) Sophisticated security mapping, including cross-domain and field-level security.
D) Support for new ?virtual multi-dimensional node? technology capable of aggregating documents created from multiple sources or tables.
3. What is the difference between Hadoop?s MapReduce and IBM?s Adaptive MapReduce feature available in InfoSphere BigInsights?
A) Hadoop?s MapReduce is optimized for operating on small files or splits, while IBM?s Adaptive MapReduce is optimized for operating on large partitioned files.
B) Hadoop?s MapReduce is optimized for operating on large files, while IBM?s Adaptive MapReduce is configurable to operate optimized on large or small files or splits.
C) Hadoop?s MapReduce is optimized for operating on small files or splits, while IBM?s Adaptive MapReduce is optimized for operating on large files stored in individual blocks.
D) Hadoop?s MapReduce is optimized for operating on small partitioned tables stored in the HBase component, while IBM?s Adaptive MapReduce is optimized for operating on large partitioned files.
4. 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.
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: B,C,D | Question # 3 Answer: B | Question # 4 Answer: B |
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