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Snowflake DEA-C01 Exam Syllabus Topics:

Topic	Details
Topic 1	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 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	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 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	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.

Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q15-Q20):

NEW QUESTION # 15
External Function is a type of UDF & can be Scaler or Tabular?

A. TRUE
B. FALSE

Answer: B

Explanation:
Explanation
External functions must be scalar functions. A scalar external function returns a single value for each input row.

NEW QUESTION # 16
A company has developed several AWS Glue extract, transform, and load (ETL) jobs to validate and transform data from Amazon S3. The ETL jobs load the data into Amazon RDS for MySQL in batches once every day. The ETL jobs use a DynamicFrame to read the S3 data.
The ETL jobs currently process all the data that is in the S3 bucket. However, the company wants the jobs to process only the daily incremental data.
Which solution will meet this requirement with the LEAST coding effort?

A. Create an ETL job that reads the S3 file status and logs the status in Amazon DynamoDB.
B. Configure the ETL jobs to delete processed objects from Amazon S3 after each run.
C. Enable job metrics for the ETL jobs to help keep track of processed objects in Amazon CloudWatch.
D. Enable job bookmarks for the ETL jobs to update the state after a run to keep track of previously processed data.

Answer: D

Explanation:
AWS Glue job bookmarks are designed to handle incremental data processing by automatically tracking the state.

NEW QUESTION # 17
A company is migrating a legacy application to an Amazon S3 based data lake. A data engineer reviewed data that is associated with the legacy application. The data engineer found that the legacy data contained some duplicate information.
The data engineer must identify and remove duplicate information from the legacy application data.
Which solution will meet these requirements with the LEAST operational overhead?

A. Write a custom extract, transform, and load (ETL) job in Python. Import the Python dedupe library. Use the dedupe library to perform data deduplication.
B. Write a custom extract, transform, and load (ETL) job in Python. Use the DataFrame.drop_duplicates() function by importing the Pandas library to perform data deduplication.
C. Write an AWS Glue extract, transform, and load (ETL) job. Use the FindMatches machine learning (ML) transform to transform the data to perform data deduplication.
D. Write an AWS Glue extract, transform, and load (ETL) job. Import the Python dedupe library. Use the dedupe library to perform data deduplication.

Answer: C

NEW QUESTION # 18
The smaller the average depth, the better clustered the table is with regards to the specified column?

A. TRUE
B. FALSE

Answer: A

NEW QUESTION # 19
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 a message to an Amazon Simple Queue Service (Amazon SQS) queue. Configure the SQS queue to invoke the Lambda function.
B. Use a second Lambda function to invoke the first Lambda function based on Amazon CloudWatch events.
C. Use the Amazon Redshift Data API to publish an event to Amazon EventBridge. Configure an EventBridge rule to invoke the Lambda function.
D. Use a second Lambda function to invoke the first Lambda function based on AWS CloudTrail events.

Answer: C

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

NEW QUESTION # 20
......

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Reliable DEA-C01 Exam Blueprint - DEA-C01 Exam Score

Snowflake DEA-C01 Exam Score, DEA-C01 Exam Dumps

Snowflake DEA-C01 Exam Syllabus Topics:

Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q15-Q20):

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