Test DEA-C01 Practice & DEA-C01 Lab Questions

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Snowflake DEA-C01 Exam Syllabus Topics:

Topic	Details
Topic 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.
Topic 2	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 3	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.
Topic 4	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 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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Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q169-Q174):

NEW QUESTION # 169
While running an external function, me following error message is received:
Error:function received the wrong number of rows
What iscausing this to occur?

A. The return message did not produce the same number of rows that it received
B. The JSON returned by the remote service is not constructed correctly
C. External functions do not support multiple rows
D. Nested arrays are not supported in the JSON response

Answer: A

Explanation:
Explanation
The error message "function received the wrong number of rows" is caused by the return message not producing the same number of rows that it received. External functions require that the remote service returns exactly one row for each input row that it receives from Snowflake. If the remote service returns more or fewer rows than expected, Snowflake will raise an error and abort the function execution. The other options are not causes of this error message. Option A is incorrect because external functions do support multiple rows as long as they match the input rows. Option B is incorrect because nested arrays are supported in the JSON response as long as they conform to the return type definition of the external function. Option C is incorrect because the JSON returned by the remote service may be constructed correctly but still produce a different number of rows than expected.

NEW QUESTION # 170
While creating External function, Which Database object required with at least ACCOUNTAD-MIN privileges?

A. SECURITY Integration
B. STORAGE Integration
C. None of the above required.
D. API Integration

Answer: D

NEW QUESTION # 171
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?

A. 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.
B. 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.
C. Use S3 Intelligent-Tiering. Activate the Deep Archive Access tier.
D. Use S3 Intelligent-Tiering. Use the default access tier.

Answer: D

NEW QUESTION # 172
A company is working on a new big data analytical tool that will store data in the EFS regional file system. Workload performance is calculated and will be 10% of the average-to-peak ratio. Data in the file system should be accessed with the lowest latency.
What performance and throughput mode can be selected?

A. Select Max I/O mode with bursting throughput mode.
B. Select general purpose mode with bursting throughput mode.
C. Select default performance mode with Provisioned throughput mode.
D. Select Max I/O mode with elastic throughput mode.

Answer: C

Explanation:
Amazon EFS provides the following performance modes
General Purpose: This is a default performance mode offering the lowest latency.
Max I/O: This mode is suitable for parallelized workloads which can withstand higher latency.
Amazon EFS offers the following throughput modes,
Elastic Throughput Mode: Suitable for spiky or unpredictable workloads or when the application requires throughput at an average-to-peak ratio of 5% or less.
Provisioned Throughput Mode: Suitable for predictable workloads or when the application requires throughput at an average-to-peak ratio of 5% or more.
Bursting Throughout Mode: Suitable when throughput needs to be scaled to the amount of storage in the file system.
In the above case, to achieve the lowest latency and throughput at 10% of the average-to-peak ratio, the default performance modes, which are the General purpose mode and the Provisioned throughput mode, can be selected.
Reference:
https://docs.aws.amazon.com/efs/latest/ug/performance.html

NEW QUESTION # 173
A retail company stores point-of-sale transaction data in an Amazon RDS for MySQL database.
The company maintains historical sales analytics in Amazon Redshift. The company needs to create daily reports that combine the current day's transactions with historical sales patterns for trend analysis. The company requires a solution that provides near real-time insights while minimizing data transfer costs and maintenance overhead.
Which solution will meet these requirements?

A. Configure AWS Database Migration Service (AWS DMS) to continuously replicate data from RDS for MySQL to Amazon Redshift. Use Redshift queries to create consolidated reports.
B. Implement Amazon Redshift federated queries to directly access RDS for MySQL data and join it with existing Redshift tables in a single query.
C. Export RDS for MySQL data to an Amazon S3 bucket on a regular schedule. Use the COPY command to load the data into Amazon Redshift staging tables. Join the data with historical data.
D. Use AWS Glue to create an extract, transform, and load (ETL) pipeline that runs every hour to copy incremental data from RDS for MySQL to Amazon Redshift. Generate reports.

Answer: A

Explanation:
AWS DMS with ongoing replication (CDC) continuously streams new RDS for MySQL transactions into Amazon Redshift, providing near real-time freshness with minimal maintenance and transferring only changes instead of full batches. Reports can then run in Redshift joining current and historical data without hourly ETL jobs or S3 staging.

NEW QUESTION # 174
......

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