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Quiz Snowflake - Efficient DEA-C01 - Test SnowPro Advanced: Data Engineer Certification Exam Cram

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Snowflake DEA-C01 Exam Syllabus Topics:

Topic
Details

Topic 1

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 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

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

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.

Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q115-Q120):

NEW QUESTION # 115
Ron, Snowflake Developer needs to capture change data (insert only) on the source views, for that he follows the below steps:
Enable change tracking on the source views & its underlying tables.
Inserted the data via Scripts scheduled with the help of Tasks.
then simply run the below Select statements.
1.select *
2.from test_table
3.changes(information => append_only)
4.at(timestamp => (select current_timestamp()));
Select the Correct Query Execution Output option below:

A. Developer missed to create stream on the source table which can further query to cap-ture DML records.
B. Select query will fail with error: 'SQL compilation error-Incorrect Keyword "Chang-es()" found'
C. Select statement complied but gives erroneous results.
D. No Error reported, select command gives Changed records with Metadata columns as change tracking enabled on the Source views & its underlying tables.

Answer: D

Explanation:
Explanation
As an alternative to streams, Snowflake supports querying change tracking metadata for tables or views using the CHANGES clause for SELECT statements. The CHANGES clause enables query-ing change tracking metadata between two points in time without having to create a stream with an explicit transactional offset.
To Know more about Snowflake CHANGES clause, please refer the mentioned link:
https://docs.snowflake.com/en/sql-reference/constructs/changes

NEW QUESTION # 116
For enabling non-ACCOUNTADMIN Roles to Perform Data Sharing Tasks, which two glob-al/account privileges snowflake provide?

A. REFERENCE USAGE
B. IMPORT SHARE
C. OPERATE
D. CREATE SHARE

Answer: B,D

Explanation:
Explanation
CREATE SHARE
In a provider account, this privilege enables creating and managing shares (for sharing data with consumer accounts).
IMPORT SHARE
In a consumer account, this privilege enables viewing the inbound shares shared with the account. Also enables creating databases from inbound shares; requires the global CREATE DATABASE privilege.
By default, these privileges are granted only to the ACCOUNTADMIN role, ensuring that only ac-count administrators can perform these tasks. However, the privileges can be granted to other roles, enabling the tasks to be delegated to other users in the account.

NEW QUESTION # 117
A company stores sensitive data in an Amazon Redshift table. The company needs to give specific users the ability to access the sensitive data. The company must not create duplication in the data.
Customer support users must be able to see the last four characters of the sensitive data. Audit users must be able to see the full value of the sensitive data. No other users can have the ability to access the sensitive information.
Which solution will meet these requirements?

A. Enable metadata security on the Redshift cluster. Create IAM users and IAM roles for the customer support users and the audit users. Grant the IAM users and IAM roles permissions to view the metadata in the Redshift cluster.
B. Create a dynamic data masking policy to allow access based on each user role. Create IAM roles that have specific access permissions. Attach the masking policy to the column that contains sensitive data.
C. Create a row-level security policy to allow access based on each user role. Create IAM roles that have specific access permissions. Attach the security policy to the table.
D. Create an AWS Glue job to redact the sensitive data and to load the data into a new Redshift table.

Answer: B

Explanation:
Amazon Redshift's dynamic data masking lets you define masking policies on sensitive columns without duplicating data. You attach a masking policy that exposes only the last four characters to customer support IAM roles, while audit IAM roles see the full values. This meets the requirement for role-based column-level access with no data duplication.

NEW QUESTION # 118
A lab uses IoT sensors to monitor humidity, temperature, and pressure for a project. The sensors send 100 KB of data every 10 seconds. A downstream process will read the data from an Amazon S3 bucket every 30 seconds.
Which solution will deliver the data to the S3 bucket with the LEAST latency?

A. Use Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) and Amazon Kinesis Data Firehose to deliver the data to the S3 bucket. Use a 5 second buffer interval for Kinesis Data Firehose.
B. Use Amazon Kinesis Data Streams to deliver the data to the S3 bucket. Configure the stream to use 5 provisioned shards.
C. Use Amazon Kinesis Data Streams and Amazon Kinesis Data Firehose to deliver the data to the S3 bucket. Use the default buffer interval for Kinesis Data Firehose.
D. Use Amazon Kinesis Data Streams and call the Kinesis Client Library to deliver the data to the S3 bucket. Use a 5 second buffer interval from an application.

Answer: A

NEW QUESTION # 119
A data engineer has implemented data quality rules in 1,000 AWS Glue Data Catalog tables.
Because of a recent change in business requirements, the data engineer must edit the data quality rules.
How should the data engineer meet this requirement with the LEAST operational overhead?

A. Create an AWS Lambda function that makes an API call to AWS Glue Data Quality to make the edits.
B. Use the AWS Management Console to edit the rules within the Data Catalog.
C. Create a pipeline in AWS Glue ETL to edit the rules for each of the 1,000 Data Catalog tables.
Use an AWS Lambda function to call the corresponding AWS Glue job for each Data Catalog table.
D. Create an Amazon EMR cluster. Run a pipeline on Amazon EMR that edits the rules for each Data Catalog table. Use an AWS Lambda function to run the EMR pipeline.

Answer: A

NEW QUESTION # 120
......

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