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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Pipeline Optimization | 20% | - ETL/ELT workflow optimization - Reduce latency and improve throughput - Design scalable and efficient data pipelines |
| Topic 2: Monitoring, Troubleshooting & Workload Management | 10% | - Bottleneck identification and resolution - Cluster resource allocation - Performance monitoring and logging |
| Topic 3: Storage & Data Management | 18% | - Distributed storage system optimization - SQL/NoSQL performance tuning - Data formats, partitioning, and indexing |
| Topic 4: Data Processing Frameworks | 22% | - Apache Spark optimization - Hadoop ecosystem tuning - Batch and real-time processing optimization |
| Topic 5: Governance, Security & Compliance | 15% | - Security and privacy protection - Data governance policies - Regulatory compliance |
| Topic 6: Streaming & IoT Data Processing | 15% | - Pravega, Kafka, NiFi usage - Real-time ingestion frameworks - Stream processing optimization |
1. What is a common approach to handling errors and failures in data pipelines?
A) Ignoring errors and continuing execution
B) Implementing robust error handling and retries
C) Relying solely on input data validation
D) Allowing errors to propagate to end-users
2. Match each Atlas feature with its description.
3. What is the purpose of sensor operators in Apache Airflow?
A) Use a poke method to monitor external processes
B) Move data sequentially from one system to another
C) Perform validation checks in parallel
D) Use triggers to report each successive retry
4. What is a data pipeline best practice related to Extract-Transform-Load (ETL) jobs?
A) A failed ETL job should always be marked as completed so that any other scheduled jobs can execute.
B) ETL jobs should be flexible to source data changes such as new variables or attributes.
C) A failed ETL job should be re-run immediately without taking any corrective actions.
D) ETL jobs should be manually executed and monitored to ensure the highest quality.
5. In Python, which non-primitive data structure can only be a collection of primitive data types?
A) Array
B) List
C) Dictionary
D) Tuple
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: Only visible for members | Question # 3 Answer: A | Question # 4 Answer: B | Question # 5 Answer: A |
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