DEA-C01유효한인증시험덤프 & DEA-C01완벽한시험덤프

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Snowflake DEA-C01 Exam Syllabus Topics:

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

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최신 SnowPro Advanced DEA-C01 무료샘플문제 (Q371-Q376):

질문 # 371
An investment company needs to manage and extract insights from a volume of semi-structured data that grows continuously.
A data engineer needs to deduplicate the semi-structured data, remove records that are duplicates, and remove common misspellings of duplicates.
Which solution will meet these requirements with the LEAST operational overhead?

정답：A


질문 # 372
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?

정답：A

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


질문 # 373
How can the following relational data be transformed into semi-structured data using the LEAST amount of operational overhead?

정답：C

설명：
Explanation
This option is the best way to transform relational data into semi-structured data using the least amount of operational overhead. The OBJECT_CONSTRUCT function takes a variable number of key-value pairs as arguments and returns a Snowflake object, which is a variant type that can store JSON data. The function can be used to convert each row of relational data into a JSON object with the column names as keys and the column values as values.


질문 # 374
A company is working on a new big data analytical tool that will store data in the EFS regional file system. Workload performance is calculated and will be 10% of the average-to-peak ratio. Data in the file system should be accessed with the lowest latency.
What performance and throughput mode can be selected?

정답：B

설명：
Amazon EFS provides the following performance modes
General Purpose: This is a default performance mode offering the lowest latency.
Max I/O: This mode is suitable for parallelized workloads which can withstand higher latency.
Amazon EFS offers the following throughput modes,
Elastic Throughput Mode: Suitable for spiky or unpredictable workloads or when the application requires throughput at an average-to-peak ratio of 5% or less.
Provisioned Throughput Mode: Suitable for predictable workloads or when the application requires throughput at an average-to-peak ratio of 5% or more.
Bursting Throughout Mode: Suitable when throughput needs to be scaled to the amount of storage in the file system.
In the above case, to achieve the lowest latency and throughput at 10% of the average-to-peak ratio, the default performance modes, which are the General purpose mode and the Provisioned throughput mode, can be selected.
Reference:
https://docs.aws.amazon.com/efs/latest/ug/performance.html


질문 # 375
A company uses Amazon RDS to store transactional data. The company runs an RDS DB instance in a private subnet. A developer wrote an AWS Lambda function with default settings to insert, update, or delete data in the DB instance.
The developer needs to give the Lambda function the ability to connect to the DB instance privately without using the public internet.
Which combination of steps will meet this requirement with the LEAST operational overhead?
(Choose two.)

정답：C,E


질문 # 376
......

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