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| Topic 1 | - 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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| 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.
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| Topic 3 | - 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 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 | - 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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Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q350-Q355):
NEW QUESTION # 350
Which functions will compute a 'fingerprint' over an entire table, query result, or window to quickly detect changes to table contents or query results? (Select TWO).
- A. HASH_AGG_COMPARE (*)
- B. HASH_AGG(*)
- C. HASH_AGG(<expr>, <expr>)
- D. HASH COMPARE(*)
- E. HASH (*)
Answer: B,C
Explanation:
Explanation
The functions that will compute a 'fingerprint' over an entire table, query result, or window to quickly detect changes to table contents or query results are:
HASH_AGG(*): This function computes a hash value over all columns and rows in a table, query result, or window. The function returns a single value for each group defined by a GROUP BY clause, or a single value for the entire input if no GROUP BY clause is specified.
HASH_AGG(<expr>, <expr>): This function computes a hash value over two expressions in a table, query result, or window. The function returns a single value for each group defined by a GROUP BY clause, or a single value for the entire input if no GROUP BY clause is specified. The other functions are not correct because:
HASH (*): This function computes a hash value over all columns in a single row. The function returns one value per row, not one value per table, query result, or window.
HASH_AGG_COMPARE (): This function compares two hash values computed by HASH_AGG() over two tables or query results and returns true if they are equal or false if they are different. The function does not compute a hash value itself, but rather compares two existing hash values.
HASH COMPARE(): This function compares two hash values computed by HASH() over two rows and returns true if they are equal or false if they are different. The function does not compute a hash value itself, but rather compares two existing hash values.
NEW QUESTION # 351
A data engineer must orchestrate a data pipeline that consists of one AWS Lambda function and one AWS Glue job. The solution must integrate with AWS services.
Which solution will meet these requirements with the LEAST management overhead?
- A. Use an AWS Glue workflow to run the Lambda function and then the AWS Glue job.
- B. Use an Apache Airflow workflow that is deployed on an Amazon EC2 instance. Define a directed acyclic graph (DAG) in which the first task is to call the Lambda function and the second task is to call the AWS Glue job.
- C. Use an Apache Airflow workflow that is deployed on Amazon Elastic Kubernetes Service (Amazon EKS). Define a directed acyclic graph (DAG) in which the first task is to call the Lambda function and the second task is to call the AWS Glue job.
- D. Use an AWS Step Functions workflow that includes a state machine. Configure the state machine to run the Lambda function and then the AWS Glue job.
Answer: D
NEW QUESTION # 352
A global finance company needs to implement near real-time cross-Region synchronization of trading data between trading centers in the us-east-1 Region, the eu-west-2 Region, and the ap- northeast-1 Region. The company must ensure that data is encrypted in transit. The solution must ensure data ordering and consistency and must support cross-Region disaster recovery.
The solution must provide data latency of less than 500 milliseconds. Which solution will meet these requirements with the LEAST operational effort?
- A. Deploy Apache Kafka Connect in each AWS Region. Use custom-developed connectors to set up cross-Region data replication. Configure the SSL security protocol.
- B. Use Amazon Managed Streaming for Apache Kafka (Amazon MSK) Replicator to establish fully interconnected replication relationships between MSK clusters in the three AWS Regions. Enable TLS encryption and IAM authentication. Set up cross-Region backup configurations.
- C. Use Amazon Kinesis Data Streams to receive trading data from each AWS Region. Use Amazon Data Firehose to replicate data between Amazon Managed Streaming for Apache Kafka (Amazon MSK) clusters in each Region. Configure AWS Key Management Service (AWS KMS) encryption and IAM roles to manage access.
- D. Deploy Apache Kafka Mirror Maker 2.0 in each AWS Region. Set up custom replication policies to handle cross-Region data synchronization. Configure the SSL security protocol.
Answer: B
Explanation:
Amazon MSK Replicator is a fully managed service for replicating data across MSK clusters in different AWS Regions, which makes it the lowest-effort option for near real-time cross-Region synchronization and disaster recovery. It supports secure encrypted connections, preserves Kafka replication behavior needed for ordered streaming data, and is designed for multi-Region resilience without requiring the company to operate custom replication infrastructure.
Reference:
https://docs.aws.amazon.com/msk/latest/developerguide/msk-replicator.html
https://docs.aws.amazon.com/msk/latest/developerguide/msk-replicator-how-it-works.html
NEW QUESTION # 353
A media company uploads large video files to Amazon S3 for processing. After processing, the company needs to keep the original files for 90 days in case the files require reprocessing. After
90 days, the company can delete the files to reduce storage costs. The company stores the processed videos in a different S3 bucket. Which S3 Lifecycle configuration will meet these requirements for the original files MOST cost-effectively?
- A. Store the files in S3 Standard for 90 days. Enable versioning. Enable Object Lock on the files for
90 days. Then expire the files. - B. Store the files in S3 Standard for 90 days. Transition the files to S3 Glacier Flexible Retrieval for long-term storage. Then expire the files.
- C. Store the files in S3 Intelligent-Tiering for 90 days. Enable versioning. Add S3 Lifecycle management to expire the files.
- D. Store the files in S3 Standard for 90 days. Implement S3 Lifecycle management to expire the files.
Answer: D
Explanation:
Keeping the files in S3 Standard for 90 days and using an S3 Lifecycle expiration rule is the most cost-effective option among the choices because the objects only need to be retained for 90 days and then deleted. Adding Glacier Flexible Retrieval would introduce archival and restore behavior intended for longer-term storage, and AWS notes that S3 Glacier Flexible Retrieval is a long-term archival class with a 90-day minimum storage duration. S3 Intelligent-Tiering also adds monitoring and automation charges, and Object Lock/versioning add unnecessary cost and controls beyond the stated requirement.
Reference:
https://docs.aws.amazon.com/AmazonS3/latest/userguide/glacier-storage-classes.html
https://docs.aws.amazon.com/AmazonS3/latest/userguide/lifecycle-expire-general- considerations.html
https://docs.aws.amazon.com/AmazonS3/latest/userguide/intelligent-tiering.html
NEW QUESTION # 354
Company A and Company B both have Snowflake accounts. Company A's account is hosted on a different cloud provider and region than Company B's account Companies A and B are not in the same Snowflake organization.
How can Company A share data with Company B? (Select TWO).
- A. Create a share within Company A's account and add Company B's account as a recipient of that share
- B. Create a new account within Company A's organization in the same cloud provider and region as Company B's account Use database replication to replicate Company A's data to the new account Create a share within the new account and add Company B's account as a recipient of that share
- C. Create a share within Company A's account, and create a reader account that is a recipient of the share Grant Company B access to the reader account
- D. Create a separate database within Company A's account to contain only those data sets they wish to share with Company B Create a share within Company A's account and add all the objects within this separate database to the share Add Company B's account as a recipient of the share
- E. Use database replication to replicate Company A's data into Company B's account Create a share within Company B's account and grant users within Company B's account access to the share
Answer: A,D
Explanation:
Explanation
The ways that Company A can share data with Company B are:
Create a share within Company A's account and add Company B's account as a recipient of that share:
This is a valid way to share data between different accounts on different cloud platforms and regions.
Snowflake supports cross-cloud and cross-region data sharing, which allows users to create shares and grant access to other accounts regardless of their cloud platform or region. However, this option may incur additional costs for network transfer and storage replication.
Create a separate database within Company A's account to contain only those data sets they wish to share with Company B Create a share within Company A'saccount and add all the objects within this separate database to the share Add Company B's account as a recipient of the share: This is also a valid way to share data between different accounts on different cloud platforms and regions. This option is similar to the previous one, except that it uses a separate database to isolate the data sets that need to be shared. This can improve security and manageability of the shared data. The other options are not valid because:
Create a share within Company A's account, and create a reader account that is a recipient of the share Grant Company B access to the reader account: This option is not valid because reader accounts are not supported for cross-cloud or cross-region data sharing. Reader accounts are Snowflake accounts that can only consume data from shares created by their provider account. Reader accounts must be on the same cloud platform and region as their provider account.
Use database replication to replicate Company A's data into Company B's account Create a share within Company B's account and grant users within Company B's account access to the share: This option is not valid because database replication cannot be used for cross-cloud or cross-region data sharing.
Database replication is a feature in Snowflake that allows users to copy databases across accounts within the same cloud platform and region. Database replication cannot copy databases across different cloud platforms or regions.
Create a new account within Company A's organization in the same cloud provider and region as Company B's account Use database replication to replicate Company A's data to the new account Create a share within the new account and add Company B's account as a recipient of that share: This option is not valid because it involves creating a new account within Company A's organization, which may not be feasible or desirable for Company A. Moreover, this option is unnecessary, as Company A can directly share data with Company B without creating an intermediate account.
NEW QUESTION # 355
......
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