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| Section | Weight | Objectives |
|---|---|---|
| Cloud Platform Overview & Snowflake Key Concepts | 8% | - Snowflake architecture layers (storage, compute, services) - Snowflake editions and features - Virtual warehouse concepts and credit usage |
| Data Sharing | 12% | - Shares and reader accounts - Reader account management - Private sharing vs. Data Exchange - Data listing marketplace |
| Databases, Tables & Views | 18% | - Stored procedures and UDFs - Data manipulation (DML operations) - Clustering and micro-partitions - Table types (permanent, transient, temporary) - Column types and sequences - Views (standard, materialized, secure) |
| Security & Access Control | 10% | - Governance best practices - Masking policies - Row-level and column-level security - Authorization (roles, privileges) - Authentication (SSO, MFA) |
| Performance Optimization & Monitoring | 4% | - Query history and monitoring - Resource optimization techniques - Query profiling and performance tuning |
| Time Travel & Cloning | 10% | - Time travel concepts and retention - UNDROP and historical data access - Zero-copy cloning - Fail-safe concepts |
| Account Objects | 8% | - Organizations and accounts structure - Resource monitors - Warehouses, databases, and schemas hierarchy |
| Virtual Warehouses | 15% | - Warehouse monitoring and troubleshooting - Warehouse sizing and scaling - Warehouse creation and configuration - Cache concepts (warehouse, result, metadata) - Multi-cluster warehouses |
| Semi-Structured Data | 10% | - Array and object operations - VARIANT data type - Parsing and flattening semi-structured data |
| Data Loading & Unloading | 15% | - Data unloading and staging - Bulk loading with COPY command - Continuous loading with Snowpipe - Data ingestion best practices - File formats (JSON, CSV, Parquet, AVRO) |
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NEW QUESTION # 154
Which Query Profile metrics will provide information that can be used to improve query performance? (Select TWO).
Answer: A,D
Explanation:
Two key metrics in Snowflake's Query Profile that provide insights for performance improvement are:
Remote Disk IO: This measures the time the query spends waiting on remote disk access, indicating potential performance issues related to I/O bottlenecks.
Pruning: This metric reflects how effectively Snowflake's micro-partition pruning is reducing the data scanned. Better pruning (more partitions excluded) leads to faster query performance, as fewer micro-partitions need to be processed.
These metrics are essential for identifying and addressing inefficiencies in data retrieval and storage access, optimizing overall query performance.
NEW QUESTION # 155
What are characteristic of Snowsight worksheet? (Select TWO.)
Answer: B,C
Explanation:
Characteristics of Snowsight worksheets in Snowflake include:
A). Worksheets can be grouped under folders, and a folder of folders: This organizational feature allows users to efficiently manage and categorize their worksheets within Snowsight, Snowflake ' s web-based UI, enhancing the user experience by keeping related worksheets together.
E). Users can import worksheets and share them with other users: Snowsight supports the sharing of worksheets among users, fostering collaboration by allowing users to share queries, analyses, and findings.
This feature is crucial for collaborative data exploration and analysis workflows.
References:
Snowflake Documentation: Snowsight (UI for Snowflake)
NEW QUESTION # 156
The Snowflake VARIANT data type imposes a 16 MB size limit on what?
Answer: C
NEW QUESTION # 157
Which clause is used to define a function that may return different values for different rows?
Answer: D
NEW QUESTION # 158
Which Snowflake tasks are managed in the cloud services layer? Select TWO.
Answer: B,D
Explanation:
The correct answers are C. Metadata management and E. Query parsing .
Snowflake's architecture has three main layers:
Cloud Services Layer
Query Processing Layer / Compute Layer
Database Storage Layer
The cloud services layer coordinates Snowflake activities and handles services such as authentication, infrastructure management, metadata management, query parsing and optimization, access control, and transaction management.
Why C is correct:
Metadata management is handled by the cloud services layer. This includes metadata about tables, micro- partitions, query optimization statistics, and access-related metadata.
Why E is correct:
Query parsing and optimization are handled by the cloud services layer before execution is assigned to compute resources.
Why the other options are incorrect:
A). Performance tuning is not usually described as a discrete cloud services task. Snowflake automatically optimizes many operations, but this option is too broad.
B). Query acceleration uses additional compute resources and is a performance feature, not a core task of the cloud services layer.
D). Query processing is performed by virtual warehouses in the compute layer, not by the cloud services layer.
Official Snowflake documentation reference:
Snowflake documentation explains that the cloud services layer manages authentication, infrastructure management, metadata, query parsing and optimization, access control, and transaction management.
Reference: Snowflake Documentation - Snowflake architecture; Snowflake Documentation - Cloud services layer; SnowPro Core Study Guide - Snowflake Architecture.
NEW QUESTION # 159
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