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Last Updated: Aug 22, 2026
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| Section | Weight | Objectives |
|---|---|---|
| The Role of the Data Engineer | 5% | - Role in analytics and data science projects - Skills and responsibilities of a data engineer |
| Building Data Pipelines with Python | 20% | - Pipeline monitoring and error handling - Python libraries for data processing - Designing and automating data pipelines |
| Data Warehousing with SQL and NoSQL | 17% | - SQL querying and performance considerations - Relational databases, schemas and normalization - NoSQL database types, features and use cases |
| Processing Streaming and IoT Data | 20% | - Apache Kafka architecture and messaging - Apache Storm and real-time processing - Streaming data concepts and IoT use cases |
| Data Governance, Security and Privacy | 20% | - Metadata management and MDM - Data privacy regulations and ethics - Big data security: Apache Atlas, Ranger, Knox - Governance frameworks, roles and policies |
| 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 |
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