最新Amazon Data-Engineer-Associate考題 & Data-Engineer-Associate證照指南

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Amazon Data-Engineer-Associate Exam Syllabus Topics:

SectionWeightObjectives
Data Security and Governance18%- Protect sensitive data
- Encrypt data at rest and in transit
- Enforce compliance and data governance
  • 1. Data lineage, audit logging, regulatory requirements
- Implement access control and authentication
  • 1. IAM, Lake Formation, resource policies
Data Store Management26%- Manage data lifecycle and storage tiers
- Design and implement data storage solutions
  • 1. S3, Redshift, DynamoDB, RDS, Lake Formation
  • 2. Data lakes, data warehouses, databases
- Optimize storage performance and cost
Data Ingestion and Transformation34%- Ingest data from various sources
  • 1. Batch and streaming data ingestion
  • 2. Use services like Kinesis, DMS, Glue, S3
- Transform and enrich data
  • 1. Apply data processing logic
  • 2. Use Spark, EMR, Step Functions
  • 3. Orchestrate data pipelines
- Implement data quality and validation
Data Operations and Support22%- Automate operational tasks
- Ensure reliability and scalability
- Backup, restore, and disaster recovery
- Monitor and troubleshoot data pipelines
  • 1. CloudWatch, X-Ray, logging and metrics

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Data-Engineer-Associate證照指南 - Data-Engineer-Associate真題材料

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最新的 AWS Certified Data Engineer Data-Engineer-Associate 免費考試真題 (Q235-Q240):

問題 #235
Creating an EventBridge rule that triggers a Lambda function on AWS Glue job failure events and then sends notifications via Amazon SNS is the most direct and operationally efficient method:
"Practice Quiz 10: A data engineer must monitor the data pipeline... Which solution will meet these requirements?

答案：

解題說明：
Inspect the job run monitoring section of the AWS Glue console.
- Ace the AWS Certified Data Engineer - Associate Certification - version 2 - apple.pdf Although this reference directly supports using AWS Glue's monitoring features via EventBridge, it implies that solutions like A-which directly use EventBridge failure events for automation-are more optimal and less complex than constructing custom logs and metrics.


問題 #236
During a security review, a company identified a vulnerability in an AWS Glue job. The company discovered that credentials to access an Amazon Redshift cluster were hard coded in the job script.
A data engineer must remediate the security vulnerability in the AWS Glue job. The solution must securely store the credentials.
Which combination of steps should the data engineer take to meet these requirements? (Choose two.)

答案：A,C

解題說明：
AWS Secrets Manager is a service that allows you to securely store and manage secrets, such as database credentials, API keys, passwords, etc. You can use Secrets Manager to encrypt, rotate, and audit your secrets, as well as to control access to them using fine-grained policies. AWS Glue is a fully managed service that provides a serverless data integration platform for data preparation, data cataloging, and data loading. AWS Glue jobs allow you to transform and load data from various sources into various targets, using either a graphical interface (AWS Glue Studio) or a code-based interface (AWS Glue console or AWS Glue API).
Storing the credentials in AWS Secrets Manager and granting the AWS Glue job 1AM role access to the stored credentials will meet the requirements, as it will remediate the security vulnerability in the AWS Glue job and securely store the credentials. By using AWS Secrets Manager, you can avoid hard coding the credentials in the job script, which is a bad practice that exposes the credentials to unauthorized access or leakage. Instead, you can store the credentials as a secret in Secrets Manager and reference the secret name or ARN in the job script. You can also use Secrets Manager to encrypt the credentials using AWS Key Management Service (AWS KMS), rotate the credentials automatically or on demand, and monitor the access to the credentials using AWS CloudTrail. By granting the AWS Glue job 1AM role access to the stored credentials, you can use the principle of least privilege to ensure that only the AWS Glue job can retrieve the credentials from Secrets Manager. You can also use resource-based or tag-based policies to further restrict the access to the credentials.
The other options are not as secure as storing the credentials in AWS Secrets Manager and granting the AWS Glue job 1AM role access to the stored credentials. Storing the credentials in the AWS Glue job parameters will not remediate the security vulnerability, as the job parameters are still visible in the AWS Glue console and API. Storing the credentials in a configuration file that is in an Amazon S3 bucket and accessing the credentials from the configuration file by using the AWS Glue job will not be as secure as using Secrets Manager, as the configuration file may not be encrypted or rotated, and the access to the file may not be audited or controlled. Reference:
AWS Secrets Manager
AWS Glue
AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide, Chapter 6: Data Integration and Transformation, Section 6.1: AWS Glue


問題 #237
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?