IBM Big Data Engineer : C2090-101

C2090-101 real exams

Exam Code: C2090-101

Exam Name: IBM Big Data Engineer

Updated: Aug 17, 2026

Q & A: 108 Questions and Answers

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What is the duration of the C2090-101 Exam

  • Format: Multiple choices, multiple answers
  • Length of Examination: 75 minutes
  • Number of Questions: 53

Reference: https://www.ibm.com/certify/exam?id=C2090-101

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IBM Big Data Engineer C2090-101 Exam

IBM Big Data Engineer C2090-101 Exam is requisite to obtain IBM Analytics Platform Certification. This IBM C2090-101 Exam validates and measures the candidate knowledge in extract data from relational source using Sqoop, Utilize Apache Hue for search Visualization, Export Processing Results out of Hadoop and utilize Consistent Regions in infosphere Streams. Big Data Engineers and Data Security Consultants usually hold or pursue this certification and you can expect the same job roles after completion of IBM Analytics Platform certification.

IBM C2090-101 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Architecture and Integration17%- Integrate GPFS and distributed file systems
- Evaluate use cases for Hive, Big SQL, and HBase
- Implement MapReduce and RDD concepts
- Design cluster architecture and storage layers
- Ensure consistent processing with InfoSphere Streams
Topic 2: Data Loading34%- Ingest data into HBase and Hive
- Load unstructured data into InfoSphere BigInsights
- Create Big SQL tables and load data into Hadoop
- Import streaming data using InfoSphere Streams
- Extract data from relational sources using Sqoop
- Load log files with Flume and command-line tools
Topic 3: Performance and Scalability15%- Tune Hive, HBase, and Big SQL performance
- Optimize query execution and workload management
- Apply best practices for latency and throughput
- Ensure high availability and scalability
Topic 4: Data Preparation, Transformation, and Export26%- Export results from Hadoop environment
- Apply Jaql for data manipulation
- Use Pig for data transformation
- Perform entity resolution and data cleansing
- Create BigSheets workbooks
Topic 5: Data Security8%- Apply data masking and redaction techniques
- Implement access control and LDAP security
- Monitor and secure sensitive data
- Comply with security standards (PCI, PII protection)
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