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| Topic | Details |
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| Topic 1 | - 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 2 | - 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 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 | - 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 5 | - 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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Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q169-Q174):
NEW QUESTION # 169
Which are the two ways to access elements in a JSON object?
- A. Use SemiColon notation to traverse a path in a JSON object:
<col-umn>:<level1_element>;<level2_element>;<level3_element>. - B. use Curly bracket notation to traverse the path in an object:
<col-umn>{'<level1_element>'}{'<level2_element>'}. - C. use bracket notation to traverse the path in an object:
<col-umn>['<level1_element>']['<level2_element>']. - D. Use dot notation to traverse a path in a JSON object:
<col-umn>:<level1_element>.<level2_element>.<level3_element>.
Answer: C,D
NEW QUESTION # 170
A data engineer must implement a data cataloging solution to track schema changes in an Amazon Redshift table.
Which solution will meet these requirements?
- A. Use the AWS Schema Conversion Tool (AWS SCT) to log the table metadata to an Apache Hive metastore. Use Amazon EventBridge Scheduler to update the metastore every day.
- B. Use AWS DataSync to log the table metadata to an AWS Glue Data Catalog. Use an AWS Glue crawler to update the Data Catalog every day.
- C. Schedule an AWS Glue crawler to run every day on the table by using the Java Database Connectivity (JDBC) driver. Configure the crawler to update an AWS Glue Data Catalog.
- D. Schedule an AWS Glue crawler to run every day on the table. Configure the crawler to update an Apache Hive metastore.
Answer: C
Explanation:
An AWS Glue crawler can connect to Amazon Redshift via JDBC, detect schema changes, and automatically update the AWS Glue Data Catalog on a schedule, providing the required ongoing schema tracking.
NEW QUESTION # 171
Does sensitive data in Snowflake is modified in an existing table while applying Masking policies?
Answer: B
Explanation:
Explanation
Snowflake supports masking policies as a schema-level object to protect sensitive data from unau-thorized access while allowing authorized users to access sensitive data at query runtime. This means that sensitive data in Snowflake is not modified in an existing table (i.e. no static masking). Rather, when users execute a query in which a masking policy applies, the masking policy condi-tions determine whether unauthorized users see masked, partially masked, obfuscated, or tokenized data.
NEW QUESTION # 172
A data engineer must maintain and monitor a data pipeline on AWS that processes streaming data from Internet of Things (IoT) devices. The pipeline uses Amazon Kinesis Data Streams to ingest data and Amazon Data Firehose to deliver data to an Amazon S3 bucket. The data engineer needs to monitor the health of the pipeline. Which solution will meet these requirements with the LEAST operational effort?
- A. Use Amazon CloudWatch Logs to manually review logs that are generated by Kinesis Data Streams and Firehose.
- B. Configure Amazon CloudWatch alarms to monitor key metrics such as IncomingBytes, OutgoingBytes, and DeliveryToS3.Success for Kinesis Data Streams and Firehose
- C. Use Amazon Managed Service for Apache Flink to perform near real-time anomaly detection on the streaming data and to invoke alerts if unusual patterns are detected.
- D. Use an AWS Lambda function to run daily checks on the status of the Kinesis Data Streams and Firehose. Configure the Lambda function to use Amazon Simple Notification Service (Amazon SNS) to send notifications.
Answer: B
Explanation:
CloudWatch metrics for Kinesis Data Streams and Firehose are available automatically and provide direct visibility into ingestion, throughput, and delivery success. Configuring CloudWatch alarms on key metrics (such as stream input/output and Firehose delivery success) enables proactive, automated health monitoring and alerting with minimal setup and no custom code or additional services to operate.
NEW QUESTION # 173
A gaming company uses a NoSQL database to store customer information. The company is planning to migrate to AWS.
The company needs a fully managed AWS solution that will handle high online transaction processing (OLTP) workload, provide single-digit millisecond performance, and provide high availability around the world.
Which solution will meet these requirements with the LEAST operational overhead?
- A. Amazon Timestream
- B. Amazon DynamoDB
- C. Amazon Keyspaces (for Apache Cassandra)
- D. Amazon DocumentDB (with MongoDB compatibility)
Answer: B
NEW QUESTION # 174
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