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Amazon Data-Engineer-Associate Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Data Ingestion and Transformation34%- Perform data ingestion
  • 1. Throughput and latency characteristics for AWS services
  • 2. Streaming data ingestion
  • 3. Replayability of data
  • 4. Batch data ingestion (scheduled ingestion, event-driven ingestion)
  • 5. Data ingestion patterns (frequency and data history)
- Orchestrate data pipelines
  • 1. AWS Glue Workflows
  • 2. Amazon Managed Workflows for Apache Airflow (MWAA)
  • 3. AWS Step Functions
  • 4. Event-driven architectures
- Apply programming concepts
  • 1. SQL, Python, Scala
  • 2. Version control
  • 3. Infrastructure as Code (IaC)
- Transform and process data
  • 1. Data transformation services (AWS Glue, Amazon EMR, AWS Lambda)
  • 2. ETL/ELT patterns
  • 3. Data partitioning and compression
  • 4. Batch and stream processing
Topic 2: Data Operations and Support22%- Automate data pipelines
  • 1. Event-driven triggers
  • 2. AWS Lambda triggers
  • 3. Scheduling jobs
- Manage and troubleshoot data processes
  • 1. Cost optimization
  • 2. Performance tuning
  • 3. Debugging failed jobs
- Monitor data pipelines
  • 1. Amazon CloudWatch
  • 2. AWS CloudTrail
  • 3. Logging and metrics
Topic 3: Data Security and Governance18%- Manage data privacy and compliance
  • 1. Data masking and tokenization
  • 2. PII data handling
  • 3. AWS Lake Formation permissions
- Implement data quality checks
  • 1. AWS Glue DataBrew
  • 2. Data validation
- Apply authentication and authorization
  • 1. Amazon S3 bucket policies
  • 2. AWS IAM policies and roles
  • 3. Service control policies (SCPs)
- Ensure data encryption
  • 1. AWS KMS
  • 2. Encryption at rest and in transit
Topic 4: Data Store Management26%- Manage data lifecycle
  • 1. Amazon S3 storage classes
  • 2. Data retention policies
  • 3. Data archiving
- Design data models
  • 1. Normalization and denormalization
  • 2. Partitioning and indexing strategies
  • 3. Schema design
- Understand data cataloging
  • 1. AWS Glue Data Catalog
  • 2. Data discovery and classification
  • 3. Schema evolution
- Choose a data store
  • 1. Data lakes vs. data warehouses
  • 2. Amazon S3, Amazon RDS, Amazon DynamoDB, Amazon Redshift
  • 3. Access and storage patterns
  • 4. Data characteristics (structured, semi-structured, unstructured)

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Amazon AWS Certified Data Engineer - Associate (DEA-C01) Sample Questions (Q216-Q221):

NEW QUESTION # 216
A data engineer needs to use AWS Step Functions to design an orchestration workflow. The workflow must parallel process a large collection of data files and apply a specific transformation to each file.
Which Step Functions state should the data engineer use to meet these requirements?

Answer: A

Explanation:
Option C is the correct answer because the Map state is designed to process a collection of data in parallel by applying the same transformation to each element. The Map state can invoke a nested workflow for each element, which can be another state machine or a Lambda function. The Map state will wait until all the parallel executions are completed before moving to the next state.
Option A is incorrect because the Parallel state is used to execute multiple branches of logic concurrently, not to process a collection of data. The Parallel state can have different branches with different logic and states, whereas the Map state has only one branch that is applied to each element of the collection.
Option B is incorrect because the Choice state is used to make decisions based on a comparison of a value to a set of rules. The Choice state does not process any data or invoke any nested workflows.
Option D is incorrect because the Wait state is used to delay the state machine from continuing for a specified time. The Wait state does not process any data or invoke any nested workflows.
Reference:
AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide, Chapter 5: Data Orchestration, Section 5.3: AWS Step Functions, Pages 131-132 Building Batch Data Analytics Solutions on AWS, Module 5: Data Orchestration, Lesson 5.2: AWS Step Functions, Pages 9-10 AWS Documentation Overview, AWS Step Functions Developer Guide, Step Functions Concepts, State Types, Map State, Pages 1-3


NEW QUESTION # 217
A company has a data warehouse that contains a table that is named Sales. The company stores the table in Amazon Redshift The table includes a column that is named city_name. The company wants to query the table to find all rows that have a city_name that starts with "San" or "El." Which SQL query will meet this requirement?