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Snowflake DEA-C01 시험요강:
| 주제 | 소개 |
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| 주제 1 | - Security: The Security topic of the DEA-C01 test covers the principles of Snowflake security, including the management of system roles and data governance. It measures the ability to secure data and ensure compliance with policies, crucial for maintaining secure data environments for Snowflake Data Engineers and Software Engineers.
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| 주제 2 | - Performance Optimization: This topic assesses the ability to optimize and troubleshoot underperforming queries in Snowflake. Candidates must demonstrate knowledge in configuring optimal solutions, utilizing caching, and monitoring data pipelines. It focuses on ensuring engineers can enhance performance based on specific scenarios, crucial for Snowflake Data Engineers and Software Engineers.
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| 주제 3 | - Data Transformation: The SnowPro Advanced: Data Engineer exam evaluates skills in using User-Defined Functions (UDFs), external functions, and stored procedures. It assesses the ability to handle semi-structured data and utilize Snowpark for transformations. This section ensures Snowflake engineers can effectively transform data within Snowflake environments, critical for data manipulation tasks.
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| 주제 4 | - Data Movement: Snowflake Data Engineers and Software Engineers are assessed on their proficiency to load, ingest, and troubleshoot data in Snowflake. It evaluates skills in building continuous data pipelines, configuring connectors, and designing data sharing solutions.
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| 주제 5 | - Storage and Data Protection: The topic tests the implementation of data recovery features and the understanding of Snowflake's Time Travel and micro-partitions. Engineers are evaluated on their ability to create new environments through cloning and ensure data protection, highlighting essential skills for maintaining Snowflake data integrity and accessibility.
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>> DEA-C01시험패스 가능한 공부문제 <<
DEA-C01완벽한 시험자료 & DEA-C01인기자격증 시험대비자료
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최신 SnowPro Advanced DEA-C01 무료샘플문제 (Q327-Q332):
질문 # 327
An ecommerce company processes millions of orders each day. The company uses AWS Glue ETL to collect data from multiple sources, clean the data, and store the data in an Amazon S3 bucket in CSV format by using the S3 Standard storage class. The company uses the stored data to conduct daily analysis.
The company wants to optimize costs for data storage and retrieval.
Which solution will meet this requirement?
- A. Configure AWS Glue ETL to transform the incoming data to Apache Parquet format.
- B. Transition the data from Amazon S3 to an Amazon Aurora cluster.
- C. Configure AWS Glue ETL to use Amazon EMR to process incoming data in parallel.
- D. Transition the data to Amazon S3 Glacier Flexible Retrieval.
정답:A
설명:
Converting the CSV files into Apache Parquet during your Glue ETL jobs dramatically reduces both storage size (because Parquet is a compressed, columnar format) and query cost (because analytics engines only scan the columns you need). This change requires no new infrastructure and pays off immediately for your daily analysis workloads.
질문 # 328
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?
- A. Create an IAM role that includes the AWSGlueServiceRole policy. Associate the role with the crawler. Specify the S3 bucket path of the source data as the crawler's data store. Allocate data processing units (DPUs) to run the crawler every day. Configure the output destination to a new path in the existing S3 bucket.
- B. Create an IAM role that includes the AmazonS3FullAccess policy. Associate the role with the crawler. Specify the S3 bucket path of the source data as the crawler's data store. Create a daily schedule to run the crawler. Configure the output destination to a new path in the existing S3 bucket.
- C. Create an IAM role that includes the AWSGlueServiceRole policy. Associate the role with the crawler. Specify the S3 bucket path of the source data as the crawler's data store. Create a daily schedule to run the crawler. Specify a database name for the output.
- D. Create an IAM role that includes the AmazonS3FullAccess policy. Associate the role with the crawler. Specify the S3 bucket path of the source data as the crawler's data store. Allocate data processing units (DPUs) to run the crawler every day. Specify a database name for the output.
정답:C
설명:
https://docs.aws.amazon.com/glue/latest/dg/tutorial-add-crawler.html
질문 # 329
A manufacturing company has many IoT devices in facilities around the world. The company uses Amazon Kinesis Data Streams to collect data from the devices. The data includes device ID, capture date, measurement type, measurement value, and facility ID. The company uses facility ID as the partition key.
The company's operations team recently observed many WriteThroughputExceeded exceptions.
The operations team found that some shards were heavily used but other shards were generally idle.
How should the company resolve the issues that the operations team observed?
- A. Archive the data on the producer's side.
- B. Increase the number of shards.
- C. Change the partition key from facility ID to capture date.
- D. Change the partition key from facility ID to a randomly generated key.
정답:D
설명:
The best solution to resolve the issue of uneven shard usage and WriteThroughputExceeded exceptions is to balance the load more evenly across the shards. This can be effectively achieved by changing the partition key to something that ensures a more uniform distribution of data across the shards.
질문 # 330
While creating External function, Which Database object required with at least ACCOUNTAD-MIN privileges?
- A. API Integration
- B. SECURITY Integration
- C. None of the above required.
- D. STORAGE Integration
정답:A
질문 # 331
A financial company recently added more features to its mobile app. The new features required the company to create a new topic in an existing Amazon Managed Streaming for Apache Kafka (Amazon MSK) cluster.
A few days after the company added the new topic, Amazon CloudWatch raised an alarm on the RootDiskUsed metric for the MSK cluster.
How should the company address the CloudWatch alarm?
- A. Expand the storage of the Apache ZooKeeper nodes.
- B. Specify the Target Volume-in-GiB parameter for the existing topic.
- C. Update the MSK broker instance to a larger instance type. Restart the MSK cluster.
- D. Expand the storage of the MSK broker. Configure the MSK cluster storage to expand automatically.
정답:D
설명:
The RootDiskUsed metric in Amazon MSK indicates that the storage space on the broker's disk is filling up. To resolve this, the company can expand the storage for the MSK brokers to prevent them from running out of disk space.
Amazon MSK supports automatic storage scaling, which can be configured to avoid similar issues in the future. By enabling auto-scaling, MSK will automatically expand the storage when needed, ensuring that the brokers have enough space to handle new topics or additional data.
ZooKeeper is used for managing the state of Kafka brokers, but the RootDiskUsed metric pertains to the Kafka brokers, not the ZooKeeper nodes.
Expanding ZooKeeper storage will not resolve the issue.
While increasing the instance size may improve performance, it does not address the issue of running out of disk space on the broker's root volume, which is causing the CloudWatch alarm.
Kafka topics do not have a direct volume specification. Storage for Kafka is managed at the broker level, not at the individual topic level. Therefore, this option does not apply to the issue of disk usage.
질문 # 332
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DEA-C01완벽한 시험자료: https://www.itcertkr.com/DEA-C01_exam.html
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