IBM Big Data Engineer: C2090-101 Exam

"IBM Big Data Engineer", also known as C2090-101 exam, is a IBM Certification. With the complete collection of questions and answers, UpdateDumps has assembled to take you through 108 Q&As to your C2090-101 Exam preparation. In the C2090-101 exam resources, you will cover every field and category in IBM Analytics: Platform Analytics Certification helping to ready you for your successful IBM Certification.

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  • Updated on: Jun 18, 2026
  • No. of Questions: 108 Questions & Answers

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  • Updated on: Jun 18, 2026
  • No. of Questions: 108 Questions & Answers

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IBM Big Data Engineer Exam Certification Details:

Duration75 mins
Exam NameIBM Certified Data Engineer - Big Data
Schedule ExamPearson VUE
Passing Score64%
Exam Price$200 (USD)
Number of Questions53
Exam CodeC2090-101
Books / TrainingIBM Knowledge Center
Sample QuestionsIBM Big Data Engineer Sample Questions

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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.

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IBM C2090-101 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Evaluate use cases for selecting potential file formats
  • Use Resilient Distributed Dataset (RDD) to improve MapReduce performance
Topic 2
  • Evaluate use cases for selecting Hive, Big SQL, or HBase
  • Create a BigSheets workbook
Topic 3
  • Utilize consistent regions in InfoSphere Streams to ensure at least once processing
  • Load log data into Hadoop using Flume
Topic 4
  • Insert data via IBM General Parallel File System (GPFS) Posix file system API
  • Use Jaql query methods to transform data in InfoSphere BigInsights
Topic 5
  • Export processing results out of Hadoop
  • Load data with Hadoop command line utility
Topic 6
  • Make specific performance tuning decisions for Hive and HBase
  • Import streaming data into Hadoop using InfoSphere Streams
Topic 7
  • Utilize Apache Hue for search visualization
  • Extract data from a relational source using Sqoop
Topic 8
  • Import data into Hadoop and create Big SQL table definitions
  • Utilize Pig for data transformation and data manipulation
Topic 9
  • Implement entity resolution within a Big Data platform
  • Load unstructured data into InfoSphere BigInsights

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

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