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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	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 3	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 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 (Q230-Q235):

NEW QUESTION # 230
What is the primary purpose of data lineage in data engineering?

A. To create visualizations.
B. To transform data formats.
C. To optimize query performance.
D. To trace the source and flow of data.

Answer: D

NEW QUESTION # 231
PARTITION_TYPE = USER_SPECIFIED must be used when you prefer to add and remove par-titions selectively rather than automatically adding partitions for all new files in an external storage location that match an expression?

A. TRUE
B. FALSE

Answer: A

Explanation:
Explanation
The CREATE EXTERNAL TABLE syntax for manually added partitions is as follows:
1.CREATE EXTERNAL TABLE
2.<table_name>
3.( <part_col_name> <col_type> AS <part_expr> )
4.[ , ... ]
5.[ PARTITION BY ( <part_col_name> [, <part_col_name> ... ] ) ]
6.PARTITION_TYPE = USER_SPECIFIED
Included the required PARTITION_TYPE = USER_SPECIFIED parameter.

NEW QUESTION # 232
A data engineer needs to deploy a serverless data pipeline. In the pipeline, CSV files are uploaded to an Amazon S3 bucket, which invokes an AWS Lambda function. The Lambda function transforms the CSV files to JSON format and stores the results in a second S3 bucket.
The data engineer has created an AWS Serverless Application Model (AWS SAM) template that includes the Lambda function. The data engineer wants to use AWS SAM for the pipeline deployment.
Which solution will package and deploy this serverless data pipeline?

A. Add the first S3 bucket and the S3 event source for the Lambda function to the SAM template. Run the sam build command to prepare the deployment package. Run the sam deploy --guided command to deploy the pipeline.
B. Run the sam deploy command directly with the --s3-bucket parameter to deploy the Lambda function code. Manually configure the S3 event trigger in the AWS Management Console.
C. Add the first S3 bucket and the S3 event source for the Lambda function to the SAM template. Run the sam build command followed by the aws cloudformation deploy command to deploy the pipeline.
D. Add the first S3 bucket to the SAM template. Run the sam package template to upload the Lambda function code to Amazon S3. Create an AWS CloudFormation stack from the packaged template. Configure event notifications manually.

Answer: A

Explanation:
AWS SAM can define both the Amazon S3 bucket and the S3 event source that invokes the Lambda function directly in the SAM template. The standard deployment flow is to run sam build to prepare the application artifacts and then run sam deploy --guided to package and deploy the serverless resources through AWS CloudFormation. This provides a complete infrastructure-as- code deployment for the pipeline without requiring manual trigger configuration.

NEW QUESTION # 233
Select the Incorrect statement about External Functions in SnowFlake?

A. Inside Snowflake, the external function is stored as a database object that contains in-formation that Snowflake uses to call the remote service.
B. An external function does not contain its own code; instead, the external function calls code that is stored and executed outside Snowflake.
C. An external function is a type of UDF.
D. Inside Snowflake, the external function is stored as a API Integration object.

Answer: D

NEW QUESTION # 234
A data engineer needs to maintain a central metadata repository that users access through Amazon EMR and Amazon Athena queries. The repository needs to provide the schema and properties of many tables. Some of the metadata is stored in Apache Hive. The data engineer needs to import the metadata from Hive into the central metadata repository.
Which solution will meet these requirements with the LEAST development effort?

A. Use a metastore on an Amazon RDS for MySQL DB instance.
B. Use Amazon EMR and Apache Ranger.
C. Use the AWS Glue Data Catalog.
D. Use a Hive metastore on an EMR cluster.

Answer: C

Explanation:
https://aws.amazon.com/blogs/big-data/metadata-classification-lineage-and-discovery-using- apache-atlas-on-amazon-emr/

NEW QUESTION # 235
......

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