DEA-C01 Exam Preparation: SnowPro Advanced: Data Engineer Certification Exam & DEA-C01 Practice Labs

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| 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.
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| Topic 2 | - 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.
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| 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.
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| Topic 4 | - 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.
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| Topic 5 | - 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.
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Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q189-Q194):
NEW QUESTION # 189
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?
Answer: B
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 # 190
A company stores data in Amazon S3 and Amazon RDS. The company needs to apply technical controls to meet security requirements. The company must generate backups of the data and retain the backups for specified retention periods. The company must protect the backups from accidental or malicious deletion during the retention periods.
Which solution will meet these requirements with the LEAST operational overhead?
- A. Create S3 buckets with versioning and Cross-Region Replication enabled. Set a backup retention period and backup window for each RDS DB instance. Use Amazon RDS automated backups.Take additional snapshots as required.
- B. Create S3 buckets with versioning and Same-Region Replication enabled. Set a backup retention period and backup window for each RDS DB instance. Use the automated backup feature of Amazon RDS. Take additional snapshots as required.
- C. Create S3 buckets with versioning and MFA Delete enabled. Set a backup retention period and backup window for each RDS DB instance. Use the automated backup feature of Amazon RDS, and take additional snapshots as required.
- D. Create a backup plan in AWS Backup. Specify the backup schedule, set window and lifecycle values, and select a backup vault. Assign the Amazon S3 and Amazon RDS resources to the backup plan. Create a vault lock in compliance mode.
Answer: D
Explanation:
AWS Backup centrally automates backups for S3 and RDS with scheduled plans and lifecycle policies, and Vault Lock (compliance mode) enforces WORM immutability to prevent modification or deletion during retention, meeting security and retention requirements with minimal administration.
NEW QUESTION # 191
A global bank is using Amazon S3 to store all financial transactions for its customers. Data is stored in multiple S3 buckets. The Security Team wants to perform a one-time assessment to determine if any credit card data is stored in one of Amazon's S3 buckets. The team will be using Amazon Macie to make this discovery.
How sensitive data can be discovered?
- A. Perform sensitive data discovery jobs with managed data identifiers.
- B. Perform automated sensitive data discovery with custom data identifiers.
- C. Perform sensitive data discovery jobs with custom data identifiers.
- D. Perform automated sensitive data discovery with managed data identifiers.
Answer: A
Explanation:
Amazon Macie can be used to automatically discover, log, and report sensitive data in Amazon S3 buckets. It can be discovered in any of the two ways, Automated Sensitive Data Discovery Job: This job can be used to get broader visibility of sensitive data stored in Amazon S3 buckets. It evaluates S3 buckets daily and identifies data.
Sensitive Data Discovery Job: It can be used to provide a deeper analysis of sensitive data from specific S3 buckets.
For discovering data in any of the above two options, further fine-tuning of the data discovery can be done in the following ways, Managed Data Identifiers: They use built-in criteria and techniques to identify known sensitive data, such as credit card and passport numbers.
Custom Data Identifier: This method uses custom data identifiers, such as regular expressions (regex), to identify any pattern or character matching the sensitive data.
Access List: This can be used to ignore specific names or characters that should not be considered sensitive data.
Reference:
https://docs.aws.amazon.com/macie/latest/user/data-classification.html
NEW QUESTION # 192
A company has a business intelligence platform on AWS. The company uses an AWS Storage Gateway Amazon S3 File Gateway to transfer files from the company's on-premises environment to an Amazon S3 bucket.
A data engineer needs to setup a process that will automatically launch an AWS Glue workflow to run a series of AWS Glue jobs when each file transfer finishes successfully.
Which solution will meet these requirements with the LEAST operational overhead?
- A. Determine when the file transfers usually finish based on previous successful file transfers. Set up an Amazon EventBridge scheduled event to initiate the AWS Glue jobs at that time of day.
- B. Set up an AWS Lambda function that will invoke the AWS Glue Workflow. Set up an event for the creation of an S3 object as a trigger for the Lambda function.
- C. Set up an on-demand AWS Glue workflow so that the data engineer can start the AWS Glue workflow when each file transfer is complete.
- D. Set up an Amazon EventBridge event that initiates the AWS Glue workflow after every successful S3 File Gateway file transfer event.
Answer: D
Explanation:
Using EventBridge directly to trigger the AWS Glue workflow upon S3 events is straightforward and leverages AWS's event-driven architecture, requiring minimal maintenance.
NEW QUESTION # 193
As a skilled data engineer, you have been tasked with managing the Spark ETL jobs that run on the EMR and store incremental data in S3. However, you have noticed that some jobs are failing, and you are eager to take proactive steps to troubleshoot the issue. What would be the primary course of action to resolve this problem and ensure the smooth operation of the ETL process?
- A. Increase the number of EC2 instances in the cluster.
- B. Restart the EMR cluster.
- C. Check the available disk space on the HDFS cluster.
- D. Review the Spark job logs for errors or warnings.
Answer: D
Explanation:
Reviewing Spark job logs is the first step to identify errors, warnings, or slow stages that indicate the root cause of the performance issue.
NEW QUESTION # 194
......
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