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Snowflake DEA-C01 Exam Syllabus Topics:

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

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Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q249-Q254):

NEW QUESTION # 249
A company is building an inventory management system and an inventory reordering system to automatically reorder products. Both systems use Amazon Kinesis Data Streams. The inventory management system uses the Amazon Kinesis Producer Library (KPL) to publish data to a stream. The inventory reordering system uses the Amazon Kinesis Client Library (KCL) to consume data from the stream. The company configures the stream to scale up and down as needed.
Before the company deploys the systems to production, the company discovers that the inventory reordering system received duplicated data.
Which factors could have caused the reordering system to receive duplicated data? (Choose two.)

Answer: B,D


NEW QUESTION # 250
A Data Engineer has developed a dashboard that will issue the same SQL select clause to Snowflake every 12 hours.
---will Snowflake use the persisted query results from the result cache provided that the underlying data has not changed

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