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| Section | Weight | Objectives |
|---|---|---|
| Time Travel & Cloning | 10% | - UNDROP and historical data access - Fail-safe concepts - Time travel concepts and retention - Zero-copy cloning |
| Performance Optimization & Monitoring | 4% | - Query history and monitoring - Query profiling and performance tuning - Resource optimization techniques |
| Data Sharing | 12% | - Private sharing vs. Data Exchange - Reader account management - Shares and reader accounts - Data listing marketplace |
| Virtual Warehouses | 15% | - Warehouse monitoring and troubleshooting - Multi-cluster warehouses - Warehouse creation and configuration - Warehouse sizing and scaling - Cache concepts (warehouse, result, metadata) |
| Cloud Platform Overview & Snowflake Key Concepts | 8% | - Virtual warehouse concepts and credit usage - Snowflake architecture layers (storage, compute, services) - Snowflake editions and features |
| Data Loading & Unloading | 15% | - Bulk loading with COPY command - Continuous loading with Snowpipe - File formats (JSON, CSV, Parquet, AVRO) - Data unloading and staging - Data ingestion best practices |
| Databases, Tables & Views | 18% | - Views (standard, materialized, secure) - Column types and sequences - Table types (permanent, transient, temporary) - Stored procedures and UDFs - Clustering and micro-partitions - Data manipulation (DML operations) |
| Security & Access Control | 10% | - Masking policies - Authorization (roles, privileges) - Authentication (SSO, MFA) - Row-level and column-level security - Governance best practices |
| Semi-Structured Data | 10% | - Parsing and flattening semi-structured data - VARIANT data type - Array and object operations |
| Account Objects | 8% | - Organizations and accounts structure - Warehouses, databases, and schemas hierarchy - Resource monitors |
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NEW QUESTION # 596
Which Snowflake feature enables loading data from cloud storage as soon as files ate available in a stage?
Answer: A
NEW QUESTION # 597
Which command should be used to unload all the rows from a table into one or more files in a named stage?
Answer: B
Explanation:
To unload data from a table into one or more files in a named stage, the COPY INTO <location> command should be used. This command exports the result of a query, such as selecting all rows from a table, into files stored in the specified stage. The COPY INTO command is versatile, supporting various file formats and compression options for efficient data unloading.
References:
Snowflake Documentation: COPY INTO Location
NEW QUESTION # 598
What is the purpose of multi-cluster virtual warehouses?
Answer: B
Explanation:
Multi-cluster virtual warehouses in Snowflake are designed to manage user and query concurrency needs. They allow for the allocation of additional clusters of compute resources, either statically or dynamically, to handle increased loads and reduce or eliminate the queuing of concurrent queries2.
https://docs.snowflake.com/en/user-guide/warehouses-multicluster.html#:~:text=Multi%2Dcluster%
20warehouses%20enable%20you,during%20peak%20and%20off%20hours.
NEW QUESTION # 599
Which command is used to start configuring Snowflake for Single Sign-On (SSO)?
Answer: B
Explanation:
To start configuring Snowflake for Single Sign-On (SSO), the CREATE SECURITY INTEGRATION command is used.This command sets up a security integration object in Snowflake, which is necessary for enabling SSO with external identity providers using SAML 2.01.
References:[COF-C02] SnowPro Core Certification Exam Study Guide
NEW QUESTION # 600
Which function can be used with the copy into <location> statement to convent rows from a relational table to a single variant column, and to unload rows into a JSON file?
Answer: B
Explanation:
The correct function to use with the COPY INTO <location> statement to convert rows from a relational table into a single variant column and to unload rows into a JSON file is TO VARIANT. The TO VARIANT function is used to explicitly convert a value of any supported data type into a VARIANT data type. This is particularly useful when needing to aggregate multiple columns or complex data structures into a single JSON-formatted string, which can then be unloaded into a file.
In the context of unloading data, the COPY INTO <location> statement combined with TO VARIANT enables the conversion of structured data from Snowflake tables into a semi-structured VARIANT format, typically JSON, which can then be efficiently exported and stored. This approach is often utilized for data integration scenarios, backups, or when data needs to be shared in a format that is easily consumed by various applications or services that support JSON.
References:
Snowflake Documentation on Data Unloading: Unloading Data
Snowflake Documentation on VARIANT Data Type: Working with JSON
NEW QUESTION # 601
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