Amazon Data-Engineer-Associate權威認證 - Data-Engineer-Associate題庫更新

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Data-Engineer-Associate題庫更新 & Data-Engineer-Associate PDF

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最新的 AWS Certified Data Engineer Data-Engineer-Associate 免費考試真題 (Q96-Q101):

問題 #96
A company has a data warehouse in Amazon Redshift. To comply with security regulations, the company needs to log and store all user activities and connection activities for the data warehouse.
Which solution will meet these requirements?

答案：A

解題說明：
Problem Analysis:
The company must log all user activities and connection activities in Amazon Redshift for security compliance.
Key Considerations:
Redshift supports audit logging, which can be configured to write logs to an S3 bucket.
S3 provides durable, scalable, and cost-effective storage for logs.
Solution Analysis:
Option A: S3 for Logging
Standard approach for storing Redshift logs.
Easy to set up and manage with minimal cost.
Option B: Amazon EFS
EFS is unnecessary for this use case and less cost-efficient than S3.
Option C: Aurora MySQL
Using a database to store logs increases complexity and cost.
Option D: EBS Volume
EBS is not a scalable option for log storage compared to S3.
Final Recommendation:
Enable Redshift audit logging and specify an S3 bucket as the destination.
Reference:
Amazon Redshift Audit Logging
Storing Logs in Amazon S3


問題 #97
A company is using Amazon Redshift to build a data warehouse solution. The company is loading hundreds of tiles into a tact table that is in a Redshift cluster.
The company wants the data warehouse solution to achieve the greatest possible throughput. The solution must use cluster resources optimally when the company loads data into the tact table.
Which solution will meet these requirements?

答案：A

解題說明：
To achieve the highest throughput and efficiently use cluster resources while loading data into an Amazon Redshift cluster, the optimal approach is to use a single COPY command that ingests data in parallel.
Option D: Use a single COPY command to load the data into the Redshift cluster.
The COPY command is designed to load data from multiple files in parallel into a Redshift table, using all the cluster nodes to optimize the load process. Redshift is optimized for parallel processing, and a single COPY command can load multiple files at once, maximizing throughput.
Options A, B, and C either involve unnecessary complexity or inefficient approaches, such as using multiple COPY commands or INSERT statements, which are not optimized for bulk loading.
Reference:
Amazon Redshift COPY Command Documentation


問題 #98
A company wants to migrate data from an Amazon RDS for PostgreSQL DB instance in the eu-east-1 Region of an AWS account named Account_A. The company will migrate the data to an Amazon Redshift cluster in the eu-west-1 Region of an AWS account named Account_B.
Which solution will give AWS Database Migration Service (AWS DMS) the ability to replicate data between two data stores?

答案：A

解題說明：
Option A is the best answer because AWS DMS documentation recommends that, when practical, you create the replication instance in the same Region as your target endpoint, and in the same VPC or subnet as your target endpoint. In this scenario, the target is the Amazon Redshift cluster in eu-west-1 in Account_B, so placing the replication instance there is the most appropriate design. AWS DMS uses the replication instance to connect to the source, read the source data, transform it as needed, and load it into the target.
This also makes architectural sense because the replication instance must have network connectivity to both endpoints, and colocating it with the Redshift target usually simplifies connectivity to the target warehouse and aligns with AWS guidance. A replication instance in Account_B, eu-west-1 can still connect to the PostgreSQL source in Account_A, eu-east-1, provided the required networking and permissions are configured. AWS DMS supports replication tasks by defining a replication instance plus source and target endpoints.
The study guide also identifies AWS DMS as the correct managed service for database migration and continuous replication scenarios, including full load and change data capture. That matches this cross-account, cross-Region migration use case.


問題 #99
A data engineering team is using an Amazon Redshift data warehouse for operational reporting. The team wants to prevent performance issues that might result from long- running queries. A data engineer must choose a system table in Amazon Redshift to record anomalies when a query optimizer identifies conditions that might indicate performance issues.
Which table views should the data engineer use to meet this requirement?

答案：A

解題說明：
The STL ALERT EVENT LOG table view records anomalies when the query optimizer identifies conditions that might indicate performance issues. These conditions include skewed data distribution, missing statistics, nested loop joins, and broadcasted data. The STL ALERT EVENT LOG table view can help the data engineer to identify and troubleshoot the root causes of performance issues and optimize the query execution plan. The other table views are not relevant for this requirement. STL USAGE CONTROL records the usage limits and quotas for Amazon Redshift resources. STL QUERY METRICS records the execution time and resource consumption of queries. STL PLAN INFO records the query execution plan and the steps involved in each query. References:
STL ALERT EVENT LOG
System Tables and Views
AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide


問題 #100
A company stores daily records of the financial performance of investment portfolios in .csv format in an Amazon S3 bucket. A data engineer uses AWS Glue crawlers to crawl the S3 data.
The data engineer must make the S3 data accessible daily in the AWS Glue Data Catalog.
Which solution will meet these requirements?

答案：B

解題說明：
To make the S3 data accessible daily in the AWS Glue Data Catalog, the data engineer needs to create a crawler that can crawl the S3 data and write the metadata to the Data Catalog. The crawler also needs to run on a daily schedule to keep the Data Catalog updated with the latest data. Therefore, the solution must include the following steps:
Create an IAM role that has the necessary permissions to access the S3 data and the Data Catalog. The AWSGlueServiceRole policy is a managed policy that grants these permissions1.
Associate the role with the crawler.
Specify the S3 bucket path of the source data as the crawler's data store. The crawler will scan the data and infer the schema and format2.
Create a daily schedule to run the crawler. The crawler will run at the specified time every day and update the Data Catalog with any changes in the data3.
Specify a database name for the output. The crawler will create or update a table in the Data Catalog under the specified database. The table will contain the metadata about the data in the S3 bucket, such as the location, schema, and classification.
Option B is the only solution that includes all these steps. Therefore, option B is the correct answer.
Option A is incorrect because it configures the output destination to a new path in the existing S3 bucket. This is unnecessary and may cause confusion, as the crawler does not write any data to the S3 bucket, only metadata to the Data Catalog.
Option C is incorrect because it allocates data processing units (DPUs) to run the crawler every day. This is also unnecessary, as DPUs are only used for AWS Glue ETL jobs, not crawlers.
Option D is incorrect because it combines the errors of option A and C. It configures the output destination to a new path in the existing S3 bucket and allocates DPUs to run the crawler every day, both of which are irrelevant for the crawler.
1: AWS managed (predefined) policies for AWS Glue - AWS Glue
2: Data Catalog and crawlers in AWS Glue - AWS Glue
3: Scheduling an AWS Glue crawler - AWS Glue
[4]: Parameters set on Data Catalog tables by crawler - AWS Glue
[5]: AWS Glue pricing - Amazon Web Services (AWS)


問題 #101
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順便提一下，可以從雲存儲中下載VCESoft Data-Engineer-Associate考試題庫的完整版：https://drive.google.com/open?id=1Yn0BxK0_p9Eo9OjWrUK2b7J7rc4ytase

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