높은통과율DEA-C01시험대비시험대비덤프공부

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Snowflake DEA-C01 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Advanced Snowflake Features10-15%- Data Sharing
  • 1. Reader accounts
  • 2. Secure share creation and management
  • 3. Direct sharing vs Data Marketplace
- External Integrations
  • 1. External functions and UDFs
  • 2. Partner integrations (Spark, Kafka, etc.)
  • 3. Snowflake Connector for Python/Java
- Data Lakes
  • 1. External tables and Iceberg support
  • 2. Snowflake as a Data Lake
  • 3. Querying semi-structured data (VARIANT, ARRAY, OBJECT)
Topic 2: Data Storage and Retrieval15-20%- Performance Optimization
  • 1. Result set caching
  • 2. Query profiling and execution plans
  • 3. Materialized views and cached results
  • 4. Warehouse scaling policies
- Snowflake Architecture
  • 1. Table types (permanent, transient, temporary)
  • 2. Hybrid and Hyper tables
  • 3. Micro-partitioning concepts
  • 4. Clustering strategies and key selection
Topic 3: Data Transformation20-25%- SQL-Based Transformations
  • 1. Data type conversions and casting
  • 2. Complex JOIN operations and optimizations
  • 3. Merge, update, and delete operations
  • 4. Window functions for advanced analytics
- Streams and Tasks
  • 1. Scheduled and event-based task execution
  • 2. Task graph design and dependencies
  • 3. Change Data Capture (CDC) with streams
  • 4. Serverless task warehouse configuration
- Data Processing Patterns
  • 1. ELT vs ETL approaches in Snowflake
  • 2. Zero Copy Cloning for data provisioning
  • 3. Time Travel for historical data access
Topic 4: Data Ingestion15-20%- Continuous Data Ingestion
  • 1. Real-time data ingestion patterns
  • 2. Snowpipe configuration and usage
  • 3. Serverless compute for Snowpipe
- Bulk Data Loading
  • 1. COPY INTO command options and best practices
  • 2. Data loading error handling and validation
  • 3. File format considerations (CSV, JSON, Parquet, Avro)
  • 4. Staging configurations (internal and external stages)
Topic 5: Data Governance and Security15-20%- Compliance and Monitoring
  • 1. Tag-based policies
  • 2. Access history and audit trails
  • 3. Data classification
- Access Control
  • 1. Role hierarchy and ownership
  • 2. Role-based access control (RBAC)
  • 3. GRANT and REVOKE operations
  • 4. Row-level and column-level security
- Data Protection
  • 1. Data re-identification risks
  • 2. External tokenization
  • 3. Secure data sharing across accounts
  • 4. Data masking and tokenization
Topic 6: Performance Engineering10-15%- Warehouse Management
  • 1. Resource monitors and cost control
  • 2. Auto-suspend and auto-resume settings
  • 3. Multi-cluster warehouse configuration
- Query Optimization
  • 1. Query rewrite and optimization techniques
  • 2. Predicate pushdown optimization
  • 3. Join elimination and simplification

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최신 SnowPro Advanced DEA-C01 무료샘플문제 (Q352-Q357):

질문 # 352
A company uses AWS Step Functions to orchestrate a data pipeline. The company has configured the Step Functions logs to push to Amazon CloudWatch Logs when the log level is FATAL The company has enabled logs for all AWS services in the pipeline.
A state named "preprocessing" invokes an AWS Lambda function named "preprocessing." The Lambda function preprocesses data before proceeding to the next state. The company needs to find error details if an error occurs during the data preprocessing.
Which CloudWatch Logs log group should the company check to find the error details?

정답：D

설명：
The actual error during data preprocessing occurs inside the AWS Lambda function execution.
Lambda automatically writes detailed execution logs, including errors and stack traces, to its CloudWatch Logs log group. Therefore, checking the Lambda log group provides the precise error details for the preprocessing failure.


질문 # 353
A Data Engineer has written a stored procedure that will run with caller's rights. The Engineer has granted ROLEA right to use this stored procedure.
What is a characteristic of the stored procedure being called using ROLEA?

정답：A

설명：
Explanation
A stored procedure that runs with caller's rights executes with the privileges of the role that calls it. Therefore, if the stored procedure accesses an object that ROLEA does not have access to, such as a table or a view, the stored procedure will fail with an insufficient privileges error. The other options are not correct because:
A stored procedure can be converted from caller's rights to owner's rights by using the ALTER PROCEDURE command with the EXECUTE AS OWNER option.
A stored procedure that runs with caller's rights executes in the context (database and schema) of the caller, not the owner.
ROLEA will be able to see the source code for the stored procedure by using the GET_DDL function or the DESCRIBE command, as long as it has usage privileges on the stored procedure.


질문 # 354
When created, a stream logically takes an initial snapshot of every row in the source object and the contents of a stream change as DML statements execute on the source table.
A Data Engineer, Sophie Created a view that queries the table and returns the CURRENT_USER and CURRENT_TIMESTAMP values for the query transaction. A Stream has been created on views to capture CDC.
Tony, another user inserted the data e.g.
insert into <table> values (1),(2),(3);
Emily, another user also inserted the data e.g.
insert into <table> values (4),(5),(6);
What will happened when Different user queries the same stream after 1 hour?

정답：A

설명：
Explanation
When User queries the stream, the stream returns the username for the user. The stream also returns the current timestamp for the query transaction in each row, NOT the timestamp when each row was inserted.


질문 # 355
A data engineer has a one-time task to read data from objects that are in Apache Parquet format in an Amazon S3 bucket. The data engineer needs to query only one column of the data.
Which solution will meet these requirements with the LEAST operational overhead?

정답：C

설명：
https://docs.aws.amazon.com/AmazonS3/latest/userguide/storage-inventory-athena-query.html S3 Select allows you to retrieve a subset of data from an object stored in S3 using simple SQL expressions. It is capable of working directly with objects in Parquet format.


질문 # 356
A data engineer wants to orchestrate a set of extract, transform, and load (ETL) jobs that run on AWS. The ETL jobs contain tasks that must run Apache Spark jobs on Amazon EMR, make API calls to Salesforce, and load data into Amazon Redshift.
The ETL jobs need to handle failures and retries automatically. The data engineer needs to use Python to orchestrate the jobs.
Which service will meet these requirements?

정답：D

설명：
Amazon Managed Workflows for Apache Airflow (Amazon MWAA) is a fully managed service that makes it easy to run Apache Airflow at scale. Airflow is a popular tool for orchestrating complex workflows, including ETL jobs, and can handle various task types such as running Apache Spark jobs on Amazon EMR, making API calls to external systems like Salesforce, and loading data into Amazon Redshift. Airflow allows you to define workflows using Python and offers built-in mechanisms for handling failures, retries, and retries automatically, making it a great fit for this use case.
While AWS Step Functions can orchestrate workflows and handle retries and errors, it is less suited for Python-based orchestration compared to Airflow. Also, Step Functions is more suited for AWS services and does not offer built-in support for external systems like Salesforce, which would require custom integrations.
AWS Glue is a serverless ETL service, but it primarily focuses on data transformation tasks. Glue does not handle orchestration of complex workflows involving non-Glue jobs, such as calling Salesforce APIs or running Spark jobs on EMR, as effectively as Airflow.
EventBridge is an event-driven service, not an orchestration service. It is designed for event- based workflows but does not offer the workflow orchestration capabilities needed for handling tasks like retries, error handling, and running complex workflows across different systems.


질문 # 357
......

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