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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.
Reference: https://www.ibm.com/certify/exam?id=C2090-101
IBM C2090-101 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Architecture and Integration | 17% | - Implement MapReduce and RDD concepts - Evaluate use cases for Hive, Big SQL, and HBase - Integrate GPFS and distributed file systems - Design cluster architecture and storage layers - Ensure consistent processing with InfoSphere Streams |
| Topic 2: Data Preparation, Transformation, and Export | 26% | - Perform entity resolution and data cleansing - Export results from Hadoop environment - Apply Jaql for data manipulation - Use Pig for data transformation - Create BigSheets workbooks |
| Topic 3: Data Loading | 34% | - Import streaming data using InfoSphere Streams - Ingest data into HBase and Hive - Load unstructured data into InfoSphere BigInsights - Create Big SQL tables and load data into Hadoop - Extract data from relational sources using Sqoop - Load log files with Flume and command-line tools |
| Topic 4: Data Security | 8% | - Comply with security standards (PCI, PII protection) - Monitor and secure sensitive data - Implement access control and LDAP security - Apply data masking and redaction techniques |
| Topic 5: Performance and Scalability | 15% | - Ensure high availability and scalability - Tune Hive, HBase, and Big SQL performance - Apply best practices for latency and throughput - Optimize query execution and workload management |
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