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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Architecture and Integration | 17% | - Ensure consistent processing with InfoSphere Streams - Implement MapReduce and RDD concepts - Design cluster architecture and storage layers - Evaluate use cases for Hive, Big SQL, and HBase - Integrate GPFS and distributed file systems |
| Topic 2: Performance and Scalability | 15% | - Tune Hive, HBase, and Big SQL performance - Optimize query execution and workload management - Apply best practices for latency and throughput - Ensure high availability and scalability |
| Topic 3: 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 |
| Topic 4: Data Loading | 34% | - Load unstructured data into InfoSphere BigInsights - Import streaming data using InfoSphere Streams - Create Big SQL tables and load data into Hadoop - Ingest data into HBase and Hive - Load log files with Flume and command-line tools - Extract data from relational sources using Sqoop |
| Topic 5: Data Preparation, Transformation, and Export | 26% | - Use Pig for data transformation - Apply Jaql for data manipulation - Create BigSheets workbooks - Export results from Hadoop environment - Perform entity resolution and data cleansing |
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