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