2026 Snowflake Valid DEA-C01: Cert SnowPro Advanced: Data Engineer Certification Exam Exam
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Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q18-Q23):
NEW QUESTION # 18
A data engineer is designing a log table for an application that requires continuous ingestion. The application must provide dependable API-based access to specific records from other applications. The application must handle more than 4,000 concurrent write operations and 6,500 read operations every second. Which solution will meet these requirements?
- A. Store the log files in an Amazon S3 Standard bucket. Register the schema in AWS Glue Data Catalog. Create an external Redshift table that points to the AWS Glue schema. Use the table to perform Amazon Redshift Spectrum read operations.
- B. Create an Amazon DynamoDB table that has provisioned capacity to meet the application's capacity needs. Use the DynamoDB table to perform all read and write operations by using DynamoDB APIs.
- C. Create an Amazon Redshift table with the KEY distribution style. Use the Amazon Redshift Data API to perform all read and write operations.
- D. Create an Amazon Redshift table with the EVEN distribution style. Use the Amazon Redshift Java Database Connectivity (JDBC) connector to establish a database connection. Use the database connection to perform all read and write operations.
Answer: B
Explanation:
Amazon DynamoDB is the best fit because it is designed for dependable API-based access with very high request rates and can be provisioned to support the required thousands of concurrent write and read operations per second. It also supports direct item retrieval and query operations through DynamoDB APIs, which matches the requirement for other applications to access specific records reliably. Amazon Redshift is designed for analytics workloads rather than high- throughput transactional API reads and writes.
Reference:
https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/read-write- operations.html
https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/Query.html
NEW QUESTION # 19
Mark the correct Statements with respect to Secure views & its creation in the SnowFlake Account?
- A. For non-materialized views, the IS_SECURE column in the Information Schema and Account Usage views identifies whether a view is secure.
- B. The internals of a secure view are not exposed in Query Profile (in the web interface). This is the case even for the owner of the secure view, because non-owners might have access to an owner's Query Profile.
- C. For a secure view, internal optimizations can indirectly expose data & the view defini-tion is visible to other users.
- D. Secure views should not be used for views that are defined solely for query conven-ience, such as views created to simplify queries for which users do not need to under-stand the underlying data representation.
- E. To convert an existing view to a secure view and back to a regular view, set/unset the SECURE keyword in the ALTER VIEW or ALTER MATERIALIZED VIEW com-mand.
Answer: A,B,D,E
Explanation:
Explanation
Why Should I Use Secure Views?
For a non-secure view, internal optimizations can indirectly expose data.
Some of the internal optimizations for views require access to the underlying data in the base tables for the view. This access might allow data that is hidden from users of the view to be exposed through user code, such as user-defined functions, or other programmatic methods. Secure views do not utilize these optimizations, ensuring that users have no access to the underlying data.
For a non-secure view, the view definition is visible to other users.
By default, the query expression used to create a standard view, also known as the view definition or text, is visible to users in various commands and interfaces.
For security or privacy reasons, you might not wish to expose the underlying tables or internal struc-tural details for a view. With secure views, the view definition and details are visible only to author-ized users (i.e.
users who are granted the role that owns the view).
When Should I Use a Secure View?
Views should be defined as secure when they are specifically designated for data privacy (i.e. to limit access to sensitive data that should not be exposed to all users of the underlying table(s)).
Secure views should not be used for views that are defined solely for query convenience, such as views created to simplify queries for which users do not need to understand the underlying data representation. Secure views can execute more slowly than non-secure views.
Secure views are defined using the SECURE keyword with the standard DDL for views:
To create a secure view, specify the SECURE keyword in the CREATE VIEW or CREATE MA-TERIALIZED VIEW command.
To convert an existing view to a secure view and back to a regular view, set/unset the SECURE keyword in the ALTER VIEW or ALTER MATERIALIZED VIEW command.
The definition of a secure view is only exposed to authorized users (i.e. users who have been grant-ed the role that owns the view). If an unauthorized user uses any of the following commands or in-terfaces, the view definition is not displayed:
SHOW VIEWS and SHOW MATERIALIZED VIEWS commands.
GET_DDL utility function.
VIEWS Information Schema view.
VIEWS Account Usage view.
For non-materialized views, the IS_SECURE column in the Information Schema and Account Us-age views identifies whether a view is secure.
The internals of a secure view are not exposed in Query Profile (in the web interface). This is the case even for the owner of the secure view, because non-owners might have access to an owner's Query Profile.
NEW QUESTION # 20
Mark the incorrect statement when Data Engineer implement Automating Continuous Data Loading Using Cloud Messaging?
- A. Triggering automated Snowpipe data loads using S3 event messages is supported by Snowflake accounts hosted on Cloud Platform like AWS, GCP or AZURE.
- B. When a pipe is paused, event messages received for the pipe enter a limited retention period. The period is 14 days by default. If a pipe is paused for longer than 14 days, it is considered stale.
- C. Automated Snowpipe uses event notifications to determine when new files arrive in monitored cloud storage and are ready to load.
- D. Notifications identify the cloud storage event and include a list of the file names. They do not include the actual data in the files.
Answer: A
Explanation:
Explanation
Triggering automated Snowpipe data loads using S3 event messages is supported by Snowflake ac-counts hosted on Amazon Web Services (AWS) only.
Rest is correct statements.
NEW QUESTION # 21
A data engineer notices slow query performance on a highly partitioned table that is in Amazon Athena. The table contains daily data for the previous 5 years, partitioned by date.
The data engineer wants to improve query performance and to automate partition management.
Which solution will meet these requirements?
- A. Use partition projection in Athena. Configure the table properties by using a date range from 5 years ago to the present.
- B. Reduce the number of partitions by changing the partitioning schema from daily to monthly granularity.
- C. Use an AWS Lambda function that runs daily. Configure the function to manually create new partitions in AWS Glue for each day's data.
- D. Increase the processing capacity of Athena queries by allocating more compute resources.
Answer: A
Explanation:
Partition projection eliminates the need for frequent metadata lookups or explicit partition registration in the AWS Glue Data Catalog. By defining a date range in your table's properties (for example, projection.enabled=true, projection.order_date.type=DATE, projection.order_date.range=2020/01/01,NOW, and the appropriate format), Athena will calculate partitions on-the-fly. This both speeds up queries (avoiding catalog calls for thousands of partitions) and removes the need for any external partition-management jobs.
NEW QUESTION # 22
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?
- A. YES
- B. NO
Answer: B
NEW QUESTION # 23
......
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