Last Updated: Aug 02, 2026
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| Section | Weight | Objectives |
|---|---|---|
| Machine Learning Model Optimization | 25% | - Model Tuning and Evaluation
|
| Deployment and Operationalization | 15% | - Model Deployment
|
| Data Preparation and Feature Engineering | 20% | - Feature Engineering Techniques
|
| Data Governance and MLOps | 15% | - Governance and Operations
|
| Data Engineering Pipeline Optimization | 25% | - Pipeline Design and Performance
|
1. What type of expertise is required to be an effective data engineer?
A) Project management
B) Accounting
C) Big Data tools
D) Business analysis
2. Which characteristic of a relational database ensures that each row in a table is uniquely identifiable?
A) Foreign key
B) Joins
C) Indexing
D) Primary key
3. What is a common approach to handling errors and failures in data pipelines?
A) Implementing robust error handling and retries
B) Relying solely on input data validation
C) Allowing errors to propagate to end-users
D) Ignoring errors and continuing execution
4. Which component of the Apache Atlas framework allows metadata to be added to the Atlas environment?
A) Apps
B) Metadata Sources
C) Graph Engine
D) Ingest/Export
5. Which of the following are components of the Apache Spark Streaming architecture? (Select all that apply)
A) Worker node
B) Kafka topics
C) Discretized streams (DStreams)
D) HDFS storage
E) Driver node
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: D | Question # 3 Answer: A | Question # 4 Answer: D | Question # 5 Answer: A,C,E |
Darnell
Ford
Humphrey
Leif
Moses
Ivan
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