IBM C2090-101 exam - in .pdf

C2090-101 pdf
  • Exam Code: C2090-101
  • Exam Name: IBM Big Data Engineer
  • Updated: Sep 18, 2026
  • Q & A: 108 Questions and Answers
  • PDF Price: $59.99
  • PDF Demo

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  • Exam Code: C2090-101
  • Exam Name: IBM Big Data Engineer
  • Updated: Sep 18, 2026
  • Q & A: 108 Questions and Answers
  • PDF Version + PC Test Engine + Online Test Engine
  • Value Pack Total: $119.98  $79.99
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IBM C2090-101 exam - Testing Engine

C2090-101 Testing Engine
  • Exam Code: C2090-101
  • Exam Name: IBM Big Data Engineer
  • Updated: Sep 18, 2026
  • Q & A: 108 Questions and Answers
  • Software Price: $59.99
  • Testing Engine

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IBM C2090-101 Exam topics

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  • Data Security: 8%
  • Architecture and Integration: 17%
  • Performance and Scalability: 15%
  • Data Loading: 34%
  • Data Preparation, Transformation, and Export: 26%

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

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The IBM Big Data Engineer C2090-101 Exam certification is an internationally-recognized validation that identifies persons who earn it as possessing skilled in IBM Analytics Platform Certification. If a candidate wants significant improvement in career growth needs enhanced knowledge, skills, and talents. The IBM Big Data Engineer C2090-101 Exam certification provides proof of this advanced knowledge and skill. If a candidate has knowledge of associated technologies and skills that are required to pass IBM Big Data Engineer C2090-101 Exam then he should take this exam.

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IBM C2090-101 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Data Collection and Ingestion14%- Data acquisition technologies
  • 1. Sqoop
  • 2. Kafka
  • 3. Flume
Topic 2: Hadoop Distributed Processing28%- Hadoop ecosystem
  • 1. HDFS architecture
  • 2. Cluster management
  • 3. YARN
  • 4. MapReduce
Topic 3: Data Transformation and Analytics24%- Data processing frameworks
  • 1. Apache Pig
  • 2. Data querying and transformation
  • 3. Apache Hive
  • 4. Apache Spark fundamentals
Topic 4: Big Data Foundations12%- Big Data concepts
  • 1. Big Data use cases
  • 2. Volume, Velocity, Variety, Veracity
  • 3. Big Data architecture fundamentals
Topic 5: Data Governance, Security and Administration22%- Operational management
  • 1. Security concepts
  • 2. Performance tuning
  • 3. Monitoring and troubleshooting
  • 4. Data governance

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