Snowflake DEA-C01 Certification Test Answers & DEA-C01 Dumps Guide

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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	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	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 (Q248-Q253):

NEW QUESTION # 248
Files from multiple data sources arrive in an Amazon S3 bucket on a regular basis. A data engineer wants to ingest new files into Amazon Redshift in near real time when the new files arrive in the S3 bucket.
Which solution will meet these requirements?

A. Use S3 Event Notifications to invoke an AWS Lambda function that loads new files into Amazon Redshift.
B. Use the query editor v2 to schedule a COPY command to load new files into Amazon Redshift.
C. Use AWS Glue job bookmarks to extract, transform, and load (ETL) load new files into Amazon Redshift.
D. Use the zero-ETL integration between Amazon Aurora and Amazon Redshift to load new files into Amazon Redshift.

Answer: A

NEW QUESTION # 249
Which of the following statements is/are incorrect regarding Fail-safe data recovery?

A. Historical data in transient tables can be recovered by Snowflake due to Operation fail-ure after the Time Travel retention period ends using Fail-safe.
B. Data stored in temporary tables is not recoverable after the table is dropped as they do not have fail-safe.
C. If downtime and the time required to reload lost data are factors, permanent tables, even with their added Fail-safe costs, may offer a better overall solution than transient tables.
D. Long-lived tables, such as fact tables, should always be defined as permanent to ensure they are fully protected by Fail-safe.
E. Short-lived tables (i.e. <1 day), such as ETL work tables, can be defined as transient to eliminate Fail-safe costs.

Answer: A

NEW QUESTION # 250
A company created an extract, transform, and load (ETL) data pipeline in AWS Glue. A data engineer must crawl a table that is in Microsoft SQL Server. The data engineer needs to extract, transform, and load the output of the crawl to an Amazon S3 bucket. The data engineer also must orchestrate the data pipeline.
Which AWS service or feature will meet these requirements MOST cost-effectively?

A. AWS Step Functions
B. Amazon Managed Workflows for Apache Airflow (Amazon MWAA)
C. AWS Glue workflows
D. AWS Glue Studio

Answer: C

Explanation:
https://aws.amazon.com/blogs/big-data/orchestrate-an-etl-pipeline-using-aws-glue-workflows- triggers-and-crawlers-with-custom-classifiers/
https://aws.amazon.com/blogs/big-data/extracting-multidimensional-data-from-microsoft-sql- server-analysis-services-using-aws-glue/

NEW QUESTION # 251
Search optimization works best to improve the performance of a query when the following condi-tions are true:[Select All that apply]

A. Search Query uses Equality predicates (for example, <column_name> = <constant>) OR Predicates that use IN.
B. The table is frequently queried on columns other than the primary cluster key.
C. Search Query uses Sort Operations.
D. The table is not clustered.

Answer: A,B,D

Explanation:
Explanation
Materialized Views works best for search query performance in case of Sort Operations. For Rest of the points Search optimization works best to improve query performance.

NEW QUESTION # 252
A company wants to migrate data from an Amazon RDS for PostgreSQL DB instance in the eu- east-1 Region of an AWS account named Account_A. The company will migrate the data to an Amazon Redshift cluster in the eu-west-1 Region of an AWS account named Account_B.
Which solution will give AWS Database Migration Service (AWS DMS) the ability to replicate data between two data stores?

A. Set up an AWS DMS replication instance in Account_B in eu-east-1.
B. Set up an AWS DMS replication instance in Account_A in eu-east-1.
C. Set up an AWS DMS replication instance in a new AWS account in eu-west-1.
D. Set up an AWS DMS replication instance in Account_B in eu-west-1.

Answer: A

Explanation:
https://docs.aws.amazon.com/dms/latest/userguide/CHAP_Target.Redshift.html#CHAP_Target.R edshift.Prerequisites

NEW QUESTION # 253
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