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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
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| Section | Weight | Objectives |
|---|---|---|
| Architecture and Integration | 17% | - 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 - Integrate GPFS and distributed file systems |
| Data Preparation, Transformation, and Export | 26% | - Use Pig for data transformation - Apply Jaql for data manipulation - Create BigSheets workbooks - Perform entity resolution and data cleansing - Export results from Hadoop environment |
| Data Security | 8% | - Implement access control and LDAP security - Apply data masking and redaction techniques - Comply with security standards (PCI, PII protection) - Monitor and secure sensitive data |
| Performance and Scalability | 15% | - Ensure high availability and scalability - Optimize query execution and workload management - Tune Hive, HBase, and Big SQL performance - Apply best practices for latency and throughput |
| Data Loading | 34% | - Extract data from relational sources using Sqoop - Load log files with Flume and command-line tools - Create Big SQL tables and load data into Hadoop - Load unstructured data into InfoSphere BigInsights - Ingest data into HBase and Hive - Import streaming data using InfoSphere Streams |
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