Snowflake DEA-C01최신덤프문제 - DEA-C01최신인증시험공부자료

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Snowflake DEA-C01 시험요강:

주제	소개
주제 1	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.
주제 2	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.
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.
주제 4	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.
주제 5	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.

>> Snowflake DEA-C01최신 덤프문제 <<

Snowflake DEA-C01최신 인증시험 공부자료 & DEA-C01최신 업데이트버전 공부문제

요즘같이 시간인즉 금이라는 시대에 시간도 절약하고 빠른 시일 내에 학습할 수 있는 PassTIP의 덤프를 추천합니다. 귀중한 시간절약은 물론이고 한번에Snowflake DEA-C01인증시험을 패스함으로 여러분의 발전공간을 넓혀줍니다.

최신 SnowPro Advanced DEA-C01 무료샘플문제 (Q89-Q94):

질문 # 89
A company has an application that uses a microservice architecture. The company hosts the application on an Amazon Elastic Kubernetes Services (Amazon EKS) cluster.
The company wants to set up a robust monitoring system for the application. The company needs to analyze the logs from the EKS cluster and the application. The company needs to correlate the cluster's logs with the application's traces to identify points of failure in the whole application request flow.
Which combination of steps will meet these requirements with the LEAST development effort?
(Choose two.)

A. Use Amazon OpenSearch to correlate the logs and traces.
B. Use Amazon CloudWatch to collect logs. Use Amazon Kinesis to collect traces.
C. Use AWS Glue to correlate the logs and traces.
D. Use FluentBit to collect logs. Use OpenTelemetry to collect traces.
E. Use Amazon CloudWatch to collect logs. Use Amazon Managed Streaming for Apache Kafka (Amazon MSK) to collect traces.

정답：A,D

설명：
FluentBit is a lightweight, efficient tool to collect, process, and forward logs from the EKS cluster.
It integrates well with AWS services like CloudWatch or OpenSearch for storing and analyzing logs. OpenTelemetry is an open-source standard for collecting distributed traces, making it ideal for monitoring and analyzing application performance in a microservice architecture. Using these tools requires minimal development effort since they are widely adopted and have strong integrations with AWS.
Amazon OpenSearch (formerly Elasticsearch) is a fully managed service that makes it easy to store, search, and analyze log data, including traces from distributed systems. It is commonly used to correlate logs and traces because it provides robust querying capabilities and visualization features (via Kibana or OpenSearch Dashboards). This solution offers the necessary tools for log-trace correlation with minimal custom development effort.
While CloudWatch is suitable for log collection, Amazon Kinesis is more suited for real-time data streaming rather than collecting traces for correlation.
Kinesis also requires more configuration and development effort compared to OpenTelemetry for tracing.
Similar to Kinesis, Amazon MSK is primarily used for data streaming rather than trace collection.
It requires additional setup and custom development for correlation compared to the more straightforward integration provided by FluentBit and OpenTelemetry.
AWS Glue is primarily used for ETL (extract, transform, load) operations in a data lake. It is not designed for real-time log and trace correlation and would require significant development effort compared to the built-in capabilities of OpenSearch.

질문 # 90
A company has an Amazon S3 based data lake. The data lake contains datasets that belong to multiple departments. The data lake ingests millions of customer records each day.
A data engineer needs to design an access and storage solution that allows departments to access only the subset of the company's dataset that each department requires. The solution must follow the principle of least privilege.
Which solution will meet these requirements with the LEAST operational effort?

A. Deploy an Amazon RDS for PostgreSQL database that has the aws_s3 extension installed.Configure AWS Step Functions events to invoke an AWS Lambda function to sync the data lake with the database.
B. Set up AWS Lake Formation. Assign LF-Tags to AWS Glue Data Catalog resources. Enable Lake Formation tag-based access control (LF-TBAC).
C. Define IAM policies and IAM roles for each department. Specify the S3 access paths from the data lake that each team can access.
D. Set up Amazon Redshift and Amazon Redshift Spectrum as the primary entry points for the data lake. Define an IAM role that Amazon Redshift can assume. Configure the IAM role to grant access to the data that is in Amazon S3.

정답：B

설명：
AWS Lake Formation with LF-Tags and LF-TBAC is designed for fine-grained, scalable access control across shared data lake resources. It lets the company grant each department access only to the datasets it needs while following least privilege, and it reduces ongoing administrative work compared with managing separate IAM policies and S3 paths for every team.

질문 # 91
A Data Engineer would like to define a file structure for loading and unloading data Where can the file structure be defined? (Select THREE)

A. pipe object
B. copy command
C. stage object
D. FILE FORMAT Object
E. MERGE command
F. INSERT command

정답：B,C,D

설명：
Explanation
The places where the file format can be defined are copy command, file format object, and stage object. These places allow specifying or referencing a file format that defines how data files are parsed and loaded into or unloaded from Snowflake tables. A file format can include various options, such as field delimiter, field enclosure, compression type, date format, etc. The other options are not places where the file format can be defined. Option B is incorrect because MERGE command is a SQL command that can merge data from one table into another based on a join condition, but it does not involve loading or unloading data files. Option D is incorrect because pipe object is a Snowflake object that can load data from an external stage into a Snowflake table using COPY statements, but it does not define or reference a file format. Option F is incorrect because INSERT command is a SQL command that can insert data into a Snowflake table from literal values or subqueries, but it does not involve loading or unloading data files.

질문 # 92
A company uses an on-premises Microsoft SQL Server database to store financial transaction data. The company migrates the transaction data from the on-premises database to AWS at the end of each month. The company has noticed that the cost to migrate data from the on-premises database to an Amazon RDS for SQL Server database has increased recently.
The company requires a cost-effective solution to migrate the data to AWS. The solution must cause minimal downtown for the applications that access the database.
Which AWS service should the company use to meet these requirements?

A. AWS Database Migration Service (AWS DMS)
B. AWS Lambda
C. AWS Direct Connect
D. AWS DataSync

정답：A

질문 # 93
A data engineer needs to run a data transformation job whenever a user adds a file to an Amazon S3 bucket. The job will run for less than 1 minute. The job must send the output through an email message to the data engineer. The data engineer expects users to add one file every hour of the day.
Which solution will meet these requirements in the MOST operationally efficient way?

A. Create a small Amazon EC2 instance that polls the S3 bucket for new files. Run transformation code on a schedule to generate the output. Use operating system commands to send email messages.
B. Run an Amazon Elastic Container Service (Amazon ECS) task to poll the S3 bucket for new files.
Run transformation code on a schedule to generate the output. Use operating system commands to send email messages.
C. Create an AWS Lambda function to transform the data. Use Amazon S3 Event Notifications to invoke the Lambda function when a new object is created. Publish the output to an Amazon Simple Notification Service (Amazon SNS) topic. Subscribe the data engineer's email account to the topic.
D. Deploy an Amazon EMR cluster. Use EMR File System (EMRFS) to access the files in the S3 bucket. Run transformation code on a schedule to generate the output to a second S3 bucket.Create an Amazon Simple Notification Service (Amazon SNS) topic. Configure Amazon S3 Event Notifications to notify the topic when a new object is created.

정답：C

설명：
An S3 event notification on ObjectCreated can directly invoke a Lambda function as soon as a new file arrives. Lambda can perform your <1 minute transformation and then publish the result to an SNS topic. With the data engineer subscribed to that topic by email, the output is delivered automatically
- no servers to manage, no polling, and minimal ongoing operations.

질문 # 94
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