Unique Top-selling DEA-C01 Exams – New 2025 Snowflake Pratice Exam [Q32-Q49]

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Unique Top-selling DEA-C01 Exams – New 2025 Snowflake Pratice Exam

SnowPro Advanced Dumps DEA-C01 Exam for Full Questions – Exam Study Guide

Snowflake DEA-C01 Exam Syllabus Topics:

Topic	Details
Topic 1	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.
Topic 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.
Topic 3	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.
Topic 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.
Topic 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.

QUESTION 32
A company stores logs in an Amazon S3 bucket. When a data engineer attempts to access several log files, the data engineer discovers that some files have been unintentionally deleted.
The data engineer needs a solution that will prevent unintentional file deletion in the future.
Which solution will meet this requirement with the LEAST operational overhead?

Manually back up the S3 bucket on a regular basis.

Enable S3 Versioning for the S3 bucket.

Configure replication for the S3 bucket.

Use an Amazon S3 Glacier storage class to archive the data that is in the S3 bucket.

QUESTION 33
A financial company wants to implement a data mesh. The data mesh must support centralized data governance, data analysis, and data access control. The company has decided to use AWS Glue for data catalogs and extract, transform, and load (ETL) operations.
Which combination of AWS services will implement a data mesh? (Choose two.)

Use Amazon Aurora for data storage. Use an Amazon Redshift provisioned cluster for data analysis.

Use Amazon S3 for data storage. Use Amazon Athena for data analysis.

Use AWS Glue DataBrew for centralized data governance and access control.

Use Amazon RDS for data storage. Use Amazon EMR for data analysis.

Use AWS Lake Formation for centralized data governance and access control.

QUESTION 34
A retail company stores data from a product lifecycle management (PLM) application in an on- premises MySQL database. The PLM application frequently updates the database when transactions occur.
The company wants to gather insights from the PLM application in near real time. The company wants to integrate the insights with other business datasets and to analyze the combined dataset by using an Amazon Redshift data warehouse.
The company has already established an AWS Direct Connect connection between the on- premises infrastructure and AWS.
Which solution will meet these requirements with the LEAST development effort?

Run a scheduled AWS Glue extract, transform, and load (ETL) job to get the MySQL database updates by using a Java Database Connectivity (JDBC) connection. Set Amazon Redshift as the destination for the ETL job.

Run a full load plus CDC task in AWS Database Migration Service (AWS DMS) to continuously replicate the MySQL database changes. Set Amazon Redshift as the destination for the task.

Use the Amazon AppFlow SDK to build a custom connector for the MySQL database to continuously replicate the database changes. Set Amazon Redshift as the destination for the connector.

Run scheduled AWS DataSync tasks to synchronize data from the MySQL database. Set Amazon Redshift as the destination for the tasks.

QUESTION 35
Database XYZ has the data_retention_time_in_days parameter set to 7 days and table xyz.public.ABC has the data_retention_time_in_daysset to 10 days.
A Developer accidentally dropped the database containing this single table 8 days ago and just discovered the mistake.
How can the table be recovered?

undrop database xyz;

create -able abc_restore as select * from xyz.public.abc at {offset => -60*60*24*8};

create table abc_restore clone xyz.public.abc at (offset => -300G*24*3);

Create a Snowflake Support case lo restore the database and tab e from “a i-safe

QUESTION 36
A CSV file around 1 TB in size is generated daily on an on-premise server A corresponding table. Internal stage, and file format have already been created in Snowflake to facilitate the data loading process How can the process of bringing the CSV file into Snowflake be automated using the LEAST amount of operational overhead?

Create a task in Snowflake that executes once a day and runs a copy into statement that references the internal stage The internal stage will read the files directly from the on-premise server and copy the newest file into the table from the on-premise server to the Snowflake table

On the on-premise server schedule a SQL file to run using SnowSQL that executes a PUT to push a specific file to the internal stage Create a task that executes once a day m Snowflake and runs a OOPY WTO statement that references the internal stage Schedule the task to start after the file lands in the internal stage

On the on-premise server schedule a SQL file to run using SnowSQL that executes a PUT to push a specific file to the internal stage. Create a pipe that runs a copy into statement that references the internal stage Snowpipe auto-ingest will automatically load the file from the internal stage when the new file lands in the internal stage.

On the on premise server schedule a Python file that uses the Snowpark Python library. The Python script will read the CSV data into a DataFrame and generate an insert into statement that will directly load into the table The script will bypass the need to move a file into an internal stage

QUESTION 37
A company has a production AWS account that runs company workloads. The company’s security team created a security AWS account to store and analyze security logs from the production AWS account. The security logs in the production AWS account are stored in Amazon CloudWatch Logs.
The company needs to use Amazon Kinesis Data Streams to deliver the security logs to the security AWS account.
Which solution will meet these requirements?

Create a destination data stream in the production AWS account. In the security AWS account, create an IAM role that has cross-account permissions to Kinesis Data Streams in the production AWS account.

Create a destination data stream in the security AWS account. Create an IAM role and a trust policy to grant CloudWatch Logs the permission to put data into the stream. Create a subscription filter in the security AWS account.

Create a destination data stream in the production AWS account. In the production AWS account, create an IAM role that has cross-account permissions to Kinesis Data Streams in the security AWS account.

QUESTION 38
A company stores petabytes of data in thousands of Amazon S3 buckets in the S3 Standard storage class. The data supports analytics workloads that have unpredictable and variable data access patterns.
The company does not access some data for months. However, the company must be able to retrieve all data within milliseconds. The company needs to optimize S3 storage costs.
Which solution will meet these requirements with the LEAST operational overhead?

Use S3 Storage Lens standard metrics to determine when to move objects to more cost- optimized storage classes. Create S3 Lifecycle policies for the S3 buckets to move objects to cost-optimized storage classes. Continue to refine the S3 Lifecycle policies in the future to optimize storage costs.

Use S3 Storage Lens activity metrics to identify S3 buckets that the company accesses infrequently. Configure S3 Lifecycle rules to move objects from S3 Standard to the S3 Standard- Infrequent Access (S3 Standard-IA) and S3 Glacier storage classes based on the age of the data.

Use S3 Intelligent-Tiering. Activate the Deep Archive Access tier.

Use S3 Intelligent-Tiering. Use the default access tier.

QUESTION 39
Which methods can be used to create a DataFrame object in Snowpark? (Select THREE)

session.jdbc_connection()

session.read.json{)

session,table()

DataFraas.writeO

session.builder()

session.sql()

QUESTION 40
For enabling non-ACCOUNTADMIN Roles to Perform Data Sharing Tasks, which two glob-al/account privileges snowflake provide?

CREATE SHARE

IMPORT SHARE

REFERENCE USAGE

OPERATE

QUESTION 41
A Data Engineer needs to know the details regarding the micro-partition layout for a table named invoice using a built-in function.
Which query will provide this information?

SELECT SYSTEM$CLUSTERING_INTFORMATICII (‘Invoice’ ) ;

SELECT $CLUSTERXNG_INFQRMATION (‘Invoice’)’

CALL SYSTEM$CLUSTERING_INFORMATION (‘Invoice’);

CALL $CLUSTERINS_INFORMATION(‘Invoice’);

QUESTION 42
A company created an extract, transform, and load (ETL) data pipeline in AWS Glue. A data engineer must crawl a table that is in Microsoft SQL Server. The data engineer needs to extract, transform, and load the output of the crawl to an Amazon S3 bucket. The data engineer also must orchestrate the data pipeline.
Which AWS service or feature will meet these requirements MOST cost-effectively?

AWS Step Functions

AWS Glue workflows

AWS Glue Studio

Amazon Managed Workflows for Apache Airflow (Amazon MWAA)

QUESTION 43
A data engineer wants to improve the performance of SQL queries in Amazon Athena that run against a sales data table.
The data engineer wants to understand the execution plan of a specific SQL statement. The data engineer also wants to see the computational cost of each operation in a SQL query.
Which statement does the data engineer need to run to meet these requirements?

EXPLAIN SELECT * FROM sales;

EXPLAIN ANALYZE FROM sales;

EXPLAIN ANALYZE SELECT * FROM sales;

EXPLAIN FROM sales;

QUESTION 44
Can the same column be specified in both a Dynamic data masking policy signature and a row ac-cess policy signature at the same time?

YES

QUESTION 45
In Which Data Modelling Technique, Data Engineer generally refer the terms Hubs & Satellites?

Data Hub

Data Vault

Star Schema

Snowflake Schema

QUESTION 46
A Data Engineer has developed a dashboard that will issue the same SQL select clause to Snowflake every 12 hours.
—will Snowflake use the persisted query results from the result cache provided that the underlying data has not changed^

12 hours

24 hours

14 days

31 days

QUESTION 47
A data engineer finished testing an Amazon Redshift stored procedure that processes and inserts data into a table that is not mission critical. The engineer wants to automatically run the stored procedure on a daily basis.
Which solution will meet this requirement in the MOST cost-effective way?

Create an AWS Lambda function to schedule a cron job to run the stored procedure.

Schedule and run the stored procedure by using the Amazon Redshift Data API in an Amazon EC2 Spot Instance.

Use query editor v2 to run the stored procedure on a schedule.

Schedule an AWS Glue Python shell job to run the stored procedure.

QUESTION 48
A Data Engineer wants to check the status of a pipe named my_pipe. The pipe is inside a database named test and a schema named Extract (case-sensitive).
Which querywill provide the status of the pipe?

SELECT FROM SYSTEM$PIPE_STATUS (”test.’extract’.my_pipe”i:

SELECT FROM SYSTEM$PIPE_STATUS (,test.,,Extracr,,.ny_pipe, i I

SELE2T * FROM SYSTEM$PIPE_STATUS < ‘ test. “Extract”, my_pipe’);

SELECT * FROM SYSTEM$PIPE_STATUS (“test. ‘extract’ .my_pipe”};

QUESTION 49
Clones can be cloned, with no limitations on the number or iterations of clones that can be created (e.g. you can create a clone of a clone of a clone, and so on), which results in a n-level hierarchy of cloned objects, each with their own portion of shared and independent data storage?

TRUE

FALSE

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Unique Top-selling DEA-C01 Exams – New 2025 Snowflake Pratice Exam [Q32-Q49]

Snowflake DEA-C01 Exam Syllabus Topics:

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