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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Cloud Platform Overview & Snowflake Key Concepts | 8% | - Snowflake architecture layers (storage, compute, services) - Snowflake editions and features - Virtual warehouse concepts and credit usage |
| Topic 2: Time Travel & Cloning | 10% | - Zero-copy cloning - Fail-safe concepts - UNDROP and historical data access - Time travel concepts and retention |
| Topic 3: Data Sharing | 12% | - Reader account management - Data listing marketplace - Private sharing vs. Data Exchange - Shares and reader accounts |
| Topic 4: Performance Optimization & Monitoring | 4% | - Query history and monitoring - Query profiling and performance tuning - Resource optimization techniques |
| Topic 5: Account Objects | 8% | - Organizations and accounts structure - Resource monitors - Warehouses, databases, and schemas hierarchy |
| Topic 6: Virtual Warehouses | 15% | - Cache concepts (warehouse, result, metadata) - Warehouse sizing and scaling - Multi-cluster warehouses - Warehouse creation and configuration - Warehouse monitoring and troubleshooting |
| Topic 7: Data Loading & Unloading | 15% | - Data unloading and staging - File formats (JSON, CSV, Parquet, AVRO) - Bulk loading with COPY command - Data ingestion best practices - Continuous loading with Snowpipe |
| Topic 8: Databases, Tables & Views | 18% | - Column types and sequences - Table types (permanent, transient, temporary) - Clustering and micro-partitions - Stored procedures and UDFs - Data manipulation (DML operations) - Views (standard, materialized, secure) |
| Topic 9: Security & Access Control | 10% | - Row-level and column-level security - Authorization (roles, privileges) - Authentication (SSO, MFA) - Governance best practices - Masking policies |
| Topic 10: Semi-Structured Data | 10% | - VARIANT data type - Parsing and flattening semi-structured data - Array and object operations |
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NEW QUESTION # 425
Which service or feature in Snowflake is used to improve the performance of certain types of lookup and analytical queries that use an extensive set of WHERE conditions?
Answer: D
Explanation:
The Search Optimization Service in Snowflake is designed to improve the performance of specific types of queries, particularly those involving extensive sets of WHERE conditions. By maintaining a search index on tables, this service can accelerate lookup and analytical queries, making it a valuable feature for optimizing query performance and reducing execution times for complex searches.
References:
Snowflake Documentation: Search Optimization Service
NEW QUESTION # 426
When a schema is cloned what happens to the tags that reside in that schema or database?
Answer: A
NEW QUESTION # 427
Which drivers or connectors are supported by Snowflake? (Select TWO)
Answer: B,D
Explanation:
Snowflake supports several official connectors and drivers, including:
* Go Snowflake Driver
* Snowflake Connector for Python
Perl, COBOL, and MongoDB drivers are not supported by Snowflake.
Reference:
Snowflake Docs: Client Drivers and Connectors
NEW QUESTION # 428
Which data type can store more than one type of data structure?
Answer: A
Explanation:
The VARIANT data type in Snowflake can store multiple types of data structures, as it is designed to hold semi-structured data.It can contain any other data type, including OBJECT and ARRAY, which allows it to represent various data structures
NEW QUESTION # 429
Which Snowflake objects can be restored using Time Travel? (Select VNO).
Answer: A,D
Explanation:
Snowflake's Time Travel feature allows users to access historical data within a specific period. This feature supports the restoration of various objects, including databases and schemas, to their previous states. Time Travel can be used for recovering dropped objects, undoing accidental changes, or analyzing data changes over time. However, it does not support user or role objects like Users and Roles, or compute resources like Virtual Warehouses.
References: Snowflake Documentation on Time Travel
NEW QUESTION # 430
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