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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Processing Streaming and IoT Data | 20% | - Apache Storm and real-time processing - Apache Kafka architecture and messaging - Streaming data concepts and IoT use cases |
| Topic 2: Data Governance, Security and Privacy | 20% | - Big data security: Apache Atlas, Ranger, Knox - Data privacy regulations and ethics - Governance frameworks, roles and policies - Metadata management and MDM |
| Topic 3: Data Warehousing with SQL and NoSQL | 17% | - Relational databases, schemas and normalization - NoSQL database types, features and use cases - SQL querying and performance considerations |
| Topic 4: ETL/ELT with Hadoop and Spark | 18% | - Hadoop ecosystem, HDFS and ingestion tools - ETL vs ELT concepts and scheduling tools - Apache Spark architecture and processing |
| Topic 5: Building Data Pipelines with Python | 20% | - Pipeline monitoring and error handling - Python libraries for data processing - Designing and automating data pipelines |
| Topic 6: The Role of the Data Engineer | 5% | - Role in analytics and data science projects - Skills and responsibilities of a data engineer |
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