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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: The Role of the Data Engineer | 5% | - Skills and responsibilities of a data engineer |
| Topic 2: Data Warehousing with SQL and NoSQL | 17% | - Relational database characteristics and performance - NoSQL tools use cases and features |
| Topic 3: Building Data Pipelines with Python | 20% | - Python programming for data pipeline development |
| Topic 4: Processing Streaming and IoT Data | 20% | - Streaming architectures (e.g., Apache Kafka, Apache Flink) - IoT data use cases and streaming tools |
| Topic 5: Extract-Transform-Load (ETL) Offload with Hadoop and Spark | 18% | - Hadoop ecosystem and Apache Spark architecture - ETL, ELT processes and schedulers |
| Topic 6: Data Governance, Security and Privacy for Big Data | 20% | - Metadata, Master Data Management and privacy considerations - Data governance roles and models |
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