Updated: Jul 28, 2026
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Reference: https://www.ibm.com/certify/exam?id=C2090-101
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.
| Certification Vendor: | IBM |
| Exam Name: | IBM Big Data Engineer |
| Exam Number: | C2090-101 |
| Passing Score: | 65% |
| Real Exam Qty: | 53 |
| Exam Format: | Multiple-choice questions, Single/multiple answer |
| Exam Duration: | 75 minutes |
| Available Languages: | English |
| Exam Price: | 200 USD |
| Certificate Validity Period: | 3 years |
| Related Certifications: | IBM Analytics: Platform Analytics |
| Recommended Training: | Hadoop and Big Data Essentials IBM BigInsights Foundations |
| Exam Registration: | IBM Certification Portal Pearson VUE Registration |
| Sample Questions: | IBM C2090-101 Sample Questions |
| Exam Way: | Proctored online or onsite at Pearson VUE test centers |
| Pre Condition: | No formal prerequisites; recommended 1-2 years of hands-on experience with Hadoop, IBM BigInsights, Hive, Pig, HBase, and SQL |
| Official Syllabus URL: | https://www.ibm.com/certify/exams/C2090-101 |
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Preparation, Transformation, and Export | 26% | - Use Pig for data transformation - Create BigSheets workbooks - Export results from Hadoop environment - Apply Jaql for data manipulation - Perform entity resolution and data cleansing |
| Topic 2: Data Loading | 34% | - Import streaming data using InfoSphere Streams - Load log files with Flume and command-line tools - Ingest data into HBase and Hive - Extract data from relational sources using Sqoop - Load unstructured data into InfoSphere BigInsights - Create Big SQL tables and load data into Hadoop |
| Topic 3: Data Security | 8% | - Implement access control and LDAP security - Monitor and secure sensitive data - Comply with security standards (PCI, PII protection) - Apply data masking and redaction techniques |
| Topic 4: Architecture and Integration | 17% | - Integrate GPFS and distributed file systems - Implement MapReduce and RDD concepts - Ensure consistent processing with InfoSphere Streams - Design cluster architecture and storage layers - Evaluate use cases for Hive, Big SQL, and HBase |
| Topic 5: Performance and Scalability | 15% | - Optimize query execution and workload management - Ensure high availability and scalability - Apply best practices for latency and throughput - Tune Hive, HBase, and Big SQL performance |
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