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IBM Big Data Engineer : C2090-101 Exam Questions
- Exam Code: C2090-101
- Exam Name: IBM Big Data Engineer
- Updated: Jul 29, 2026
- Q&As: 108 Questions and Answers
About IBM Big Data Engineer Exam Braindumps
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Certification Path
The IBM Certified Specialist Certification certification includes only one exam IBM C2090-101 exam.
IBM C2090-101 Exam topics
Candidates must know the exam topics before they start of preparation. Because it will really help them in hitting the core. Our C2090-101 exam dumps will include the following topics:
- Performance and Scalability: 15%
- Architecture and Integration: 17%
- Data Loading: 34%
- Data Security: 8%
- Data Preparation, Transformation, and Export: 26%
How much C2090-101 Exam Cost
The price of the C2090-101 exam is $200 USD.
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How to study the C2090-101 Exam
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Reference: https://www.ibm.com/certify/exam?id=C2090-101
IBM C2090-101 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Architecture and Integration | 17% | - Integrate GPFS and distributed file systems - Design cluster architecture and storage layers - Implement MapReduce and RDD concepts - Evaluate use cases for Hive, Big SQL, and HBase - Ensure consistent processing with InfoSphere Streams |
| Topic 2: Data Preparation, Transformation, and Export | 26% | - Create BigSheets workbooks - Apply Jaql for data manipulation - Export results from Hadoop environment - Use Pig for data transformation - Perform entity resolution and data cleansing |
| Topic 3: Data Loading | 34% | - Import streaming data using InfoSphere Streams - Create Big SQL tables and load data into Hadoop - Load unstructured data into InfoSphere BigInsights - Extract data from relational sources using Sqoop - Load log files with Flume and command-line tools - Ingest data into HBase and Hive |
| Topic 4: Performance and Scalability | 15% | - Apply best practices for latency and throughput - Optimize query execution and workload management - Tune Hive, HBase, and Big SQL performance - Ensure high availability and scalability |
| Topic 5: Data Security | 8% | - Implement access control and LDAP security - Apply data masking and redaction techniques - Comply with security standards (PCI, PII protection) - Monitor and secure sensitive data |
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