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IBM Big Data Engineer : C2090-101

C2090-101

Exam Code: C2090-101

Exam Name: IBM Big Data Engineer

Updated: Oct 26, 2026

Q & A: 108 Questions and Answers

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About IBM Big Data Engineer certification

How to book the C2090-101 Exam

These are following steps for registering the C2090-101 exam. Step 1: Visit to Pearson Exam Registration Step 2: Signup/Login to Pearson VUE account Step 3: Search for IBM C2090-101 Exam Certifications Exam Step 4: Select Date, time and confirm with payment method

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

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:

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

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C2090-101 Exam Reference

What is the duration of the C2090-101 Exam

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

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IBM C2090-101 Exam Syllabus Topics:

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

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