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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	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 3	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 4	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 5	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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Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q351-Q356):

NEW QUESTION # 351
A Data Engineer defines the following masking policy:

....
must be applied to the full_name column in the customer table:

Which query will apply the masking policy on the full_name column?

A. ALTER TABLE customer MODIFY COLUMN first_name ADD MASKING POLICY name_policy,
B. ALTER TABLE customer MODIFY COLUMN full_name Set MASKING POLICY name_policy;
C. ALTER TABLE customer MODIFY COLUMN full_nam ADD MASKING POLICY name_poiicy;
D. ALTER TABLE customer MODIFY COLUMN first_nane SET MASKING POLICY name_policy; lasT_name SET MASKING POLICY name_pclicy;

Answer: B

Explanation:
Explanation
The query that will apply the masking policy on the full_name column is ALTER TABLE customer MODIFY COLUMN full_name SET MASKING POLICY name_policy;. This query will modify the full_name column and associate it with the name_policy masking policy, which will mask the first and last names of the customers with asterisks. The other options are incorrect because they do not follow the correct syntax for applying a masking policy on a column. Option B is incorrect because it uses ADD instead of SET, which is not a valid keyword for modifying a column. Option C is incorrect because it tries to apply the masking policy on two columns, first_name and last_name, which are not part of the table structure. Option D is incorrect because it uses commas instead of dots to separate the database, schema, and table names

NEW QUESTION # 352
Which output is provided by both theSYSTEM$CLUSTERING_DEPTHfunction and theSYSTEM$CLUSTERING_INFORMATIONfunction?

A. average_overlaps
B. total_partition_count
C. notes
D. average_depth

Answer: D

Explanation:
Explanation
The output that is provided by both the SYSTEM$CLUSTERING_DEPTH function and the SYSTEM$CLUSTERING_INFORMATION function is average_depth. This output indicates the average number of micro-partitions that contain data for a given column value or combinationof column values. The other outputs are not common to both functions. The notes output is only provided by the SYSTEM$CLUSTERING_INFORMATION function and it contains additional information or recommendations about the clustering status of the table. The average_overlaps output is only provided by the SYSTEM$CLUSTERING_DEPTH function and it indicates the average number of micro-partitions that overlap with other micro-partitions for a given column value or combination of column values. The total_partition_count output is only provided by the SYSTEM$CLUSTERING_INFORMATION function and it indicates the total number of micro-partitions in the table.

NEW QUESTION # 353
Which privilege are required on an object (i.e. user or role) with USERADMIN Role can modify the object properties?

A. OPEARTE
B. OWNERSHIP
C. MANAGE GRANTS
D. MODIFY

Answer: B

NEW QUESTION # 354
A company has a frontend ReactJS website that uses Amazon API Gateway to invoke REST APIs. The APIs perform the functionality of the website. A data engineer needs to write a Python script that can be occasionally invoked through API Gateway. The code must return results to API Gateway.
Which solution will meet these requirements with the LEAST operational overhead?

A. Deploy a custom Python script that can integrate with API Gateway on Amazon Elastic Kubernetes Service (Amazon EKS).
B. Create an AWS Lambda function. Ensure that the function is warm by scheduling an Amazon EventBridge rule to invoke the Lambda function every 5 minutes by using mock events.
C. Create an AWS Lambda Python function with provisioned concurrency.
D. Deploy a custom Python script on an Amazon Elastic Container Service (Amazon ECS) cluster.

Answer: C

Explanation:
AWS Lambda functions can be easily integrated with Amazon API Gateway to create RESTful APIs. This integration allows API Gateway to directly invoke the Lambda function when the API endpoint is hit.

NEW QUESTION # 355
A data engineer is using an AWS Glue ETL job to remove outdated customer records from a table that contains customer account information. The data engineer is using the following SQL command to remove customers that exist in a table named monthly_accounts_update table from the customer accounts table:
MERGE INTO accounts t USING monthly_accounts_update s
ON t.customer = s.customer
WHEN MATCHED
THEN DELETE
What will happen when the data engineer runs the SQL command?

A. All customer records that exist in both the customer accounts table and the monthly_accounts_update table will be deleted from the accounts table.
B. Only customer records that are present in both tables will be retained in the customer accounts table.
C. The monthly_accounts_update table will be deleted.
D. No records will be deleted because the command syntax is not valid in AWS Glue.

Answer: A

Explanation:
That MERGE statement deletes every row in accounts where the customer value matches a row in monthly_accounts_update. All overlapping customer records will be removed from the accounts table.

NEW QUESTION # 356
......

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