REAL SNOWFLAKE ARA-C01 EXAM QUESTIONS & ARA-C01 PASS4SURE EXAM PREP

Real Snowflake ARA-C01 Exam Questions & ARA-C01 Pass4sure Exam Prep

Real Snowflake ARA-C01 Exam Questions & ARA-C01 Pass4sure Exam Prep

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The SnowPro Advanced Architect Certification is a valuable credential for data architects and engineers who want to demonstrate their expertise in designing and implementing complex Snowflake solutions. SnowPro Advanced Architect Certification certification provides a competitive edge to professionals by showcasing their skills and knowledge in the field of data management, warehousing, and analytics. SnowPro Advanced Architect Certification certification is recognized globally by companies that use Snowflake for their data management needs.

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In order to prepare for the SnowPro Advanced Architect Certification exam, candidates can take advantage of various resources provided by Snowflake, such as training courses, study guides, and practice exams. Additionally, candidates can also benefit from hands-on experience working with Snowflake's cloud data platform, as well as collaborating with other Snowflake experts and architects.

Achieving the SnowPro Advanced Architect Certification demonstrates a high level of proficiency and expertise in designing and implementing complex data solutions with Snowflake. SnowPro Advanced Architect Certification certification can enhance an individual's career opportunities and provide a competitive edge in the rapidly growing field of cloud data management.

Snowflake SnowPro Advanced Architect Certification Sample Questions (Q153-Q158):

NEW QUESTION # 153
Data is being imported and stored as JSON in a VARIANT column. Query performance was fine, but most recently, poor query performance has been reported.
What could be causing this?

  • A. There were variations in string lengths for the JSON values in the recent data imports.
  • B. The recent data imports contained fewer fields than usual.
  • C. There were JSON nulls in the recent data imports.
  • D. The order of the keys in the JSON was changed.

Answer: D

Explanation:
Data is being imported and stored as JSON in a VARIANT column. Query performance was fine, but most recently, poor query performance has been reported. This could be caused by the following factors:
The order of the keys in the JSON was changed. Snowflake stores semi-structured data internally in a column-like structure for the most common elements, and the remainder in a leftovers-like column. The order of the keys in the JSON affects how Snowflake determines the common elements and how it optimizes the query performance. If the order of the keys in the JSON was changed, Snowflake might have to re-parse the data and re-organize the internal storage, which could result in slower query performance.
There were variations in string lengths for the JSON values in the recent data imports. Non-native values, such as dates and timestamps, are stored as strings when loaded into a VARIANT column. Operations on these values could be slower and also consume more space than when stored in a relational column with the corresponding data type. If there were variations in string lengths for the JSON values in the recent data imports, Snowflake might have to allocate more space and perform more conversions, which could also result in slower query performance.
The other options are not valid causes for poor query performance:
There were JSON nulls in the recent data imports. Snowflake supports two types of null values in semi-structured data: SQL NULL and JSON null. SQL NULL means the value is missing or unknown, while JSON null means the value is explicitly set to null. Snowflake can distinguish between these two types of null values and handle them accordingly. Having JSON nulls in the recent data imports should not affect the query performance significantly.
The recent data imports contained fewer fields than usual. Snowflake can handle semi-structured data with varying schemas and fields. Having fewer fields than usual in the recent data imports should not affect the query performance significantly, as Snowflake can still optimize the data ingestion and query execution based on the existing fields.
Reference:
Considerations for Semi-structured Data Stored in VARIANT
Snowflake Architect Training
Snowflake query performance on unique element in variant column
Snowflake variant performance


NEW QUESTION # 154
The Data Engineering team at a large manufacturing company needs to engineer data coming from many sources to support a wide variety of use cases and data consumer requirements which include:
1) Finance and Vendor Management team members who require reporting and visualization
2) Data Science team members who require access to raw data for ML model development
3) Sales team members who require engineered and protected data for data monetization What Snowflake data modeling approaches will meet these requirements? (Choose two.)

  • A. Create a set of profile-specific databases that aligns data with usage patterns.
  • B. Create a raw database for landing and persisting raw data entering the data pipelines.
  • C. Create a single star schema in a single database to support all consumers' requirements.
  • D. Create a Data Vault as the sole data pipeline endpoint and have all consumers directly access the Vault.
  • E. Consolidate data in the company's data lake and use EXTERNAL TABLES.

Answer: C,D


NEW QUESTION # 155
Which security, governance, and data protection features require, at a MINIMUM, the Business Critical edition of Snowflake? (Choose two.)

  • A. Extended Time Travel (up to 90 days)
  • B. Federated authentication and SSO
  • C. Periodic rekeying of encrypted data
  • D. Customer-managed encryption keys through Tri-Secret Secure
  • E. AWS, Azure, or Google Cloud private connectivity to Snowflake

Answer: D,E

Explanation:
According to the SnowPro Advanced: Architect documents and learning resources, the security, governance, and data protection features that require, at a minimum, the Business Critical edition of Snowflake are:
Customer-managed encryption keys through Tri-Secret Secure. This feature allows customers to manage their own encryption keys for data at rest in Snowflake, using a combination of three secrets: a master key, a service key, and a security password. This provides an additional layer of security and control over the data encryption and decryption process1.
Periodic rekeying of encrypted data. This feature allows customers to periodically rotate the encryption keys for data at rest in Snowflake, using either Snowflake-managed keys or customer-managed keys. This enhances the security and protection of the data by reducing the risk of key compromise or exposure2.
The other options are incorrect because they do not require the Business Critical edition of Snowflake. Option A is incorrect because extended Time Travel (up to 90 days) is available with the Enterprise edition of Snowflake3. Option D is incorrect because AWS, Azure, or Google Cloud private connectivity to Snowflake is available with the Standard edition of Snowflake4. Option E is incorrect because federated authentication and SSO are available with the Standard edition of Snowflake5. Reference: Tri-Secret Secure | Snowflake Documentation, Periodic Rekeying of Encrypted Data | Snowflake Documentation, Snowflake Editions | Snowflake Documentation, Snowflake Network Policies | Snowflake Documentation, Configuring Federated Authentication and SSO | Snowflake Documentation


NEW QUESTION # 156
A Snowflake Architect is designing an application and tenancy strategy for an organization where strong legal isolation rules as well as multi-tenancy are requirements.
Which approach will meet these requirements if Role-Based Access Policies (RBAC) is a viable option for isolating tenants?

  • A. Create an object for each tenant strategy if row level security is viable for isolating tenants.
  • B. Create a multi-tenant table strategy if row level security is not viable for isolating tenants.
  • C. Create accounts for each tenant in the Snowflake organization.
  • D. Create an object for each tenant strategy if row level security is not viable for isolating tenants.

Answer: D

Explanation:
This approach meets the requirements of strong legal isolation and multi-tenancy. By creating separate accounts for each tenant, the application can ensure that each tenant has its own dedicated storage, compute, and metadata resources, as well as its own encryption keys and security policies. This provides the highest level of isolation and data protection among the tenancy models. Furthermore, by creating the accounts within the same Snowflake organization, the application can leverage the features of Snowflake Organizations, such as centralized billing, account management, and cross-account data sharing.
Reference:
Snowflake Organizations Overview | Snowflake Documentation
Design Patterns for Building Multi-Tenant Applications on Snowflake


NEW QUESTION # 157
A group of Data Analysts have been granted the role analyst role. They need a Snowflake database where they can create and modify tables, views, and other objects to load with their own data. The Analysts should not have the ability to give other Snowflake users outside of their role access to this data.
How should these requirements be met?

  • A. Make every schema in the database a managed access schema, owned by SYSADMIN, and grant create privileges on each schema to the ANALYST_ROLE for each type of object that needs to be created.
  • B. Grant SYSADMIN ownership of the database, but grant the create schema privilege on the database to the ANALYST_ROLE.
  • C. Grant ANALYST_R0LE OWNERSHIP on the database, but make sure that ANALYST_ROLE does not have the MANAGE GRANTS privilege on the account.
  • D. Grant ANALYST_ROLE ownership on the database, but grant the ownership on future [object type] s in database privilege to SYSADMIN.

Answer: C

Explanation:
Granting ANALYST_ROLE OWNERSHIP on the database allows the analysts to create and modify tables, views, and other objects within the database. However, to prevent the analysts from giving other Snowflake users outside of their role access to this data, the ANALYST_ROLE should not have the MANAGE GRANTS privilege on the account. The MANAGE GRANTS privilege enables a role to grant or revoke privileges on any object in the account, regardless of the ownership of the object1. Therefore, by removing this privilege from the ANALYST_ROLE, the analysts can only grant or revoke privileges on the objects that they own within the database, and not on any other objects in the account2.
The other options are not correct because:
* B. Granting SYSADMIN ownership of the database and granting the create schema privilege on the database to the ANALYST_ROLE would allow the analysts to create schemas within the database, but not to create or modify tables, views, or other objects within those schemas. The analysts would need to have the create [object type] privilege on each schema to create or modify objects within the schema3.
* C. Making every schema in the database a managed access schema, owned by SYSADMIN, and granting create privileges on each schema to the ANALYST_ROLE for each type of object that needs to be created would allow the analysts to create and modify objects within the schemas, but not to grant or revoke privileges on those objects. A managed access schema is a schema that requires explicit grants for any access to the objects within the schema, regardless of the ownership of the objects4. Therefore, the analysts would need to have the grant privilege on each schema to grant or revoke privileges on the objects within the schema.
* D. Granting ANALYST_ROLE ownership on the database and granting the ownership on future [object type] s in database privilege to SYSADMIN would allow the analysts to create and modify objects within the database, but also to grant or revoke privileges on those objects. The ownership on future
* [object type] s in database privilege enables a role to automatically become the owner of any new object of the specified type that is created in the database. Therefore, by granting this privilege to SYSADMIN, the analysts would not be able to prevent SYSADMIN from accessing or modifying the objects that they create within the database.
References:
* 1: MANAGE GRANTS Privilege | Snowflake Documentation
* 2: Access Control Privileges | Snowflake Documentation
* 3: CREATE SCHEMA | Snowflake Documentation
* 4: Managed Access | Snowflake Documentation
* : GRANT | Snowflake Documentation
* : Ownership on Future Objects | Snowflake Documentation
* : Ownership and Revoking Privileges | Snowflake Documentation


NEW QUESTION # 158
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