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Snowflake DEA-C01 Exam Syllabus Topics:

Section	Weight	Objectives
Data Transformation	20-25%	- Data Processing Patterns 1. Time Travel for historical data access 2. ELT vs ETL approaches in Snowflake 3. Zero Copy Cloning for data provisioning - SQL-Based Transformations 1. Complex JOIN operations and optimizations 2. Window functions for advanced analytics 3. Merge, update, and delete operations 4. Data type conversions and casting - Streams and Tasks 1. Change Data Capture (CDC) with streams 2. Task graph design and dependencies 3. Serverless task warehouse configuration 4. Scheduled and event-based task execution
Data Governance and Security	15-20%	- Compliance and Monitoring 1. Tag-based policies 2. Access history and audit trails 3. Data classification - Access Control 1. GRANT and REVOKE operations 2. Role-based access control (RBAC) 3. Row-level and column-level security 4. Role hierarchy and ownership - Data Protection 1. Data re-identification risks 2. External tokenization 3. Secure data sharing across accounts 4. Data masking and tokenization
Data Storage and Retrieval	15-20%	- Performance Optimization 1. Query profiling and execution plans 2. Warehouse scaling policies 3. Result set caching 4. Materialized views and cached results - Snowflake Architecture 1. Hybrid and Hyper tables 2. Micro-partitioning concepts 3. Clustering strategies and key selection 4. Table types (permanent, transient, temporary)
Performance Engineering	10-15%	- Warehouse Management 1. Multi-cluster warehouse configuration 2. Resource monitors and cost control 3. Auto-suspend and auto-resume settings - Query Optimization 1. Predicate pushdown optimization 2. Query rewrite and optimization techniques 3. Join elimination and simplification
Advanced Snowflake Features	10-15%	- Data Sharing 1. Direct sharing vs Data Marketplace 2. Secure share creation and management 3. Reader accounts - Data Lakes 1. Querying semi-structured data (VARIANT, ARRAY, OBJECT) 2. External tables and Iceberg support 3. Snowflake as a Data Lake - External Integrations 1. Partner integrations (Spark, Kafka, etc.) 2. External functions and UDFs 3. Snowflake Connector for Python/Java
Data Ingestion	15-20%	- Continuous Data Ingestion 1. Real-time data ingestion patterns 2. Serverless compute for Snowpipe 3. Snowpipe configuration and usage - Bulk Data Loading 1. Data loading error handling and validation 2. COPY INTO command options and best practices 3. Staging configurations (internal and external stages) 4. File format considerations (CSV, JSON, Parquet, Avro)

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Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q346-Q351):

NEW QUESTION # 346
A data engineer is using an AWS Glue crawler to catalog data that is in an Amazon S3 bucket.
The S3 bucket contains both .csv and json files. The data engineer configured the crawler to exclude the .json files from the catalog.
When the data engineer runs queries in Amazon Athena, the queries also process the excluded .json files. The data engineer wants to resolve this issue. The data engineer needs a solution that will not affect access requirements for the .csv files in the source S3 bucket.
Which solution will meet this requirement with the SHORTEST query times?

A. Adjust the AWS Glue crawler settings to ensure that the AWS Glue crawler also excludes .json files.
B. Relocate the .json files to a different path within the S3 bucket.
C. Use the Athena console to ensure the Athena queries also exclude the .json files.
D. Use S3 bucket policies to block access to the .json files.

Answer: B

Explanation:
Athena does not recognize exclude patterns that you specify an AWS Glue crawler. For example, if you have an Amazon S3 bucket that contains both .csv and .json files and you exclude the .json files from the crawler, Athena queries both groups of files. To avoid this, place the files that you want to exclude in a different location.
https://docs.aws.amazon.com/athena/latest/ug/troubleshooting-athena.html

NEW QUESTION # 347
A company loads transaction data for each day into Amazon Redshift tables at the end of each day. The company wants to have the ability to track which tables have been loaded and which tables still need to be loaded.
A data engineer wants to store the load statuses of Redshift tables in an Amazon DynamoDB table. The data engineer creates an AWS Lambda function to publish the details of the load statuses to DynamoDB.
How should the data engineer invoke the Lambda function to write load statuses to the DynamoDB table?

A. Use the Amazon Redshift Data API to publish an event to Amazon EventBridge. Configure an EventBridge rule to invoke the Lambda function.
B. Use a second Lambda function to invoke the first Lambda function based on AWS CloudTrail events.
C. Use a second Lambda function to invoke the first Lambda function based on Amazon CloudWatch events.
D. Use the Amazon Redshift Data API to publish a message to an Amazon Simple Queue Service (Amazon SQS) queue. Configure the SQS queue to invoke the Lambda function.

Answer: A

Explanation:
https://docs.aws.amazon.com/redshift/latest/mgmt/data-api-monitoring-events.html

NEW QUESTION # 348
A retail company has a customer data hub in an Amazon S3 bucket. Employees from many countries use the data hub to support company-wide analytics. A governance team must ensure that the company's data analysts can access data only for customers who are within the same country as the analysts.
Which solution will meet these requirements with the LEAST operational effort?

A. Load the data into Amazon Redshift. Create a view for each country. Create separate IAM roles for each country to provide access to data from each country. Assign the appropriate roles to the analysts.
B. Register the S3 bucket as a data lake location in AWS Lake Formation. Use the Lake Formation row-level security features to enforce the company's access policies.
C. Move the data to AWS Regions that are close to the countries where the customers are. Provide access to each analyst based on the country that the analyst serves.
D. Create a separate table for each country's customer data. Provide access to each analyst based on the country that the analyst serves.

Answer: B

Explanation:
https://docs.aws.amazon.com/lake-formation/latest/dg/register-data-lake.html
https://docs.aws.amazon.com/lake-formation/latest/dg/registration-role.html

NEW QUESTION # 349
A data engineer is configuring Amazon SageMaker Studio to use AWS Glue interactive sessions to prepare data for machine learning (ML) models.
The data engineer receives an access denied error when the data engineer tries to prepare the data by using SageMaker Studio.
Which change should the engineer make to gain access to SageMaker Studio?

A. Add a policy to the data engineer's IAM user that includes the sts:AssumeRole action for the AWS Glue and SageMaker service principals in the trust policy.
B. Add a policy to the data engineer's IAM user that allows the sts:AddAssociation action for the AWS Glue and SageMaker service principals in the trust policy.
C. Add the AWSGlueServiceRole managed policy to the data engineer's IAM user.
D. Add the AmazonSageMakerFullAccess managed policy to the data engineer's IAM user.

Answer: D

Explanation:
Amazon SageMaker requires permissions to perform actions on your behalf. By attaching the AmazonSageMakerFullAccess managed policy to the data engineer's IAM user, you grant the necessary permissions for SageMaker Studio to access AWS Glue and other related services.

NEW QUESTION # 350
Bob, a Lead Data Engineer is looking out to get the function definition & queried below statement to check if this function is secure enough to use in his script or not.
select is_secure from information_schema.functions where function_name = 'JOHNFUNCTION'; From the query output he is sure that, Function is secure UDF, what are the way provided by snow-flake to get the function definition of secure UDF?

A. Declaring a UDF as "secure" hide the definition from Bob & all the required Definition commands will throw error.
B. He can get the secure UDF definition using GET_DDL utility function.
C. UDF definition or text, is visible to users via Query Profile (in the web interface).
D. SHOW FUNCTIONS Commands

Answer: A

NEW QUESTION # 351
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