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Snowflake AI Data Cloud Features & Architecture

Understand Snowflake's unique architecture including cloud services, query processing, and data storage layers (24% of exam).

This domain covers Snowflake's multi-cluster shared data architecture, the separation of storage and compute, the cloud services layer, virtual warehouses, metadata management, data sharing capabilities, and support for structured, semi-structured, and unstructured data. Understanding these architectural components is fundamental to effectively using Snowflake.
5 minutes 5 Questions

Snowflake AI Data Cloud is a cloud-native platform designed for data warehousing, data lakes, data engineering, data science, and secure data sharing. Here are the key features and architecture components: **Architecture Layers:** 1. **Cloud Services Layer**: This intelligent layer manages infras…

Concepts covered: Snowflake's multi-cluster shared data architecture, Separation of storage and compute, Cloud services layer, Query processing layer, Database storage layer, Virtual warehouses overview, Metadata management, Structured data in Snowflake, Semi-structured data support (JSON, Avro, Parquet, ORC, XML), Unstructured data support, Database objects (databases, schemas, tables), Table types (permanent, temporary, transient, external), Views and secure views, Snowflake editions and features, Cloud platforms (AWS, Azure, GCP), Snowflake regions and cross-cloud capabilities

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COF-C02 - Snowflake AI Data Cloud Features & Architecture Example Questions

Test your knowledge of Snowflake AI Data Cloud Features & Architecture

Question 1

A technology conglomerate is architecting their global Snowflake strategy after acquiring three regional companies. The parent company operates on AWS in US-West-2, while the acquired entities use: Azure in UK South (British subsidiary), GCP in Tokyo (Japanese division), and AWS in São Paulo (Brazilian unit). The enterprise architect must design a data mesh where each regional entity publishes curated data products that other entities can consume. During the design workshop, the integration lead questions whether all four accounts can participate equally in cross-cloud data sharing arrangements. The architect needs to clarify the technical feasibility of establishing bidirectional data sharing relationships across this heterogeneous cloud environment. What should the enterprise architect explain about implementing data sharing across these four accounts on three different cloud providers?

Correct Answer: Cross-cloud data sharing requires database replication to a target region first, as native data sharing only works between accounts within the same cloud region

The correct answer explains that cross-cloud data sharing requires database replication to a target region first, as native data sharing only works between accounts within the same cloud region.

This is accurate because Snowflake's native Secure Data Sharing feature has a fundamental architectural constraint: it only works between accounts that reside in the same cloud provider AND the same region. When sharing data across different cloud providers (AWS, Azure, GCP) or across different regions, you must first replicate the database to the target cloud/region using Snowflake's database replication feature. Once the data is replicated to the target region, you can then use standard data sharing within that region.

For the scenario described with four accounts across AWS US-West-2, Azure UK South, GCP Tokyo, and AWS São Paulo, bidirectional data sharing would require setting up database replication between the regions first, then establishing data shares from the replicated databases.

The other answers are incorrect:

  • The answer about a 'global data fabric layer' that automatically routes queries is fictional. Snowflake does not have such a mechanism that transparently routes queries across clouds for data sharing.

  • The answer suggesting cross-cloud data sharing is 'supported natively' requiring only cloud interconnect configuration is misleading. While Snowflake does support cross-cloud scenarios, it's not through native direct sharing - it requires the replication step first.

  • The answer about a 'unified metadata catalog' enabling transparent query federation is also incorrect. Snowflake does not provide automatic query federation across different cloud deployments for data sharing purposes.

Question 2

A regional credit union is modernizing their member data platform on Snowflake. During the architecture review, their data governance lead outlines the following scenario: they need to implement dynamic data masking to protect Social Security numbers when accessed by call center representatives, require object tagging capabilities to classify data sensitivity levels across their data warehouse, and want to leverage search optimization service to speed up member account lookups in their 500-million-row transaction history table. Their information security officer confirms that while they process sensitive financial data, their current audit framework does not require customer-controlled encryption key management, and their network security policies can be satisfied with standard cloud connectivity. The credit union's budget committee questions whether the Enterprise edition is sufficient or if Business Critical licensing is warranted for this specific feature combination. Which assessment correctly identifies the minimum edition required?

Correct Answer: Enterprise edition is sufficient because dynamic data masking, object tagging, and search optimization service are all available at the Enterprise tier and do not require Business Critical features

Enterprise edition is sufficient for this credit union's requirements. Let's analyze each feature mentioned:

Dynamic Data Masking: This feature, which allows masking of sensitive data like Social Security numbers based on user roles, is available starting at the Enterprise edition.

Object Tagging: The ability to tag objects for data classification and governance purposes is an Enterprise edition feature.

Search Optimization Service: This service, which accelerates point lookup queries on large tables (like the 500-million-row transaction history table mentioned), is also available at the Enterprise edition tier.

The question explicitly states that the credit union does NOT require:
- Customer-controlled encryption key management (Tri-Secret Secure) - a Business Critical feature
- Enhanced network security beyond standard cloud connectivity - Business Critical provides features like AWS PrivateLink, Azure Private Link, etc.

The other options are incorrect for these reasons:

  • The claim that search optimization requires enhanced security validation at higher tiers is false. Search Optimization Service is a performance feature available at Enterprise edition and has no special security tier requirements.

  • Object tagging does NOT require an additional license add-on. It is included as part of the Enterprise edition features.

  • Dynamic data masking does not require Business Critical for compliance certifications. The masking functionality itself is an Enterprise feature. Business Critical provides additional security features like enhanced encryption and HIPAA/PCI compliance support, but masking SSNs does not inherently require Business Critical edition.

Question 3

What is the maximum length in characters that can be stored in a VARCHAR data type in Snowflake?

Correct Answer: 16,777,216 characters (16 MB)

The correct answer is 16,777,216 characters (16 MB).

In Snowflake, the VARCHAR (also known as STRING or TEXT) data type can store a maximum of 16,777,216 characters, which equals 16 MB. This is a significant feature of Snowflake's architecture that allows for storing very large string values.

The other answers are incorrect for the following reasons:

  • 4,000 characters is the default length when you declare a VARCHAR without specifying a length in Snowflake, but it is NOT the maximum. This value is often confused with traditional database systems like Oracle where VARCHAR2 has a 4,000-byte limit.

  • 65,535 characters is a limit associated with other database systems (like MySQL's TEXT type) but does not apply to Snowflake's VARCHAR.

  • 8,388,608 characters (8 MB) is simply incorrect - Snowflake's maximum is twice this amount at 16 MB.

It's important to note that while Snowflake allows up to 16 MB for VARCHAR, the actual storage consumed depends on the actual length of the data stored, making it storage-efficient.

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