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| Section | Weight | Objectives |
|---|---|---|
| Snowflake Architecture | 30% | - Data sharing architecture design - Development lifecycle and workload support - Data protection and recovery strategies - Object hierarchy and architectural impact - Data modeling and use cases |
| Performance Optimization | 20% | - Clustering and partitioning strategies - Query performance tuning - Virtual warehouse configuration and sizing - Cost optimization and resource management |
| Data Engineering | 25% | - Transformation and processing frameworks - Data loading and unloading solutions - Data pipeline and integration design |
| Accounts and Security | 25% | - Security principles and implementation scenarios - Account and database strategy design - Security, compliance and governance architecture |
This version is designed especially for those ARA-C01 test takers who cannot go through extensive Snowflake ARA-C01 practice sessions due to a shortage of time. Since the Snowflake ARA-C01 PDF file works on smartphones, laptops, and tablets, one can use Snowflake ARA-C01 dumps without limitations of place and time. Additionally, these Snowflake ARA-C01 PDF questions are printable as well.
NEW QUESTION # 218
An Architect on a new project has been asked to design an architecture that meets Snowflake security, compliance, and governance requirements as follows:
1) Use Tri-Secret Secure in Snowflake
2) Share some information stored in a view with another Snowflake customer
3) Hide portions of sensitive information from some columns
4) Use zero-copy cloning to refresh the non-production environment from the production environment To meet these requirements, which design elements must be implemented? (Choose three.)
Answer: B,D,E
NEW QUESTION # 219
Assuming all Snowflake accounts are using an Enterprise edition or higher, in which development and testing scenarios would be copying of data be required, and zero-copy cloning not be suitable? (Select TWO).
Answer: A,B
Explanation:
Zero-copy cloning is a feature that allows creating a clone of a table, schema, or database without physically copying the data. Zero-copy cloning is suitable for scenarios where the cloned object needs to have the same data and metadata as the original object, and where the cloned object does not need to be modified or updated frequently. Zero-copy cloning is also suitable for scenarios where the cloned object needs to be shared within the same Snowflake account or across different accounts in the same cloud region2 However, zero-copy cloning is not suitable for scenarios where the cloned object needs to have different data or metadata than the original object, or where the cloned object needs to be modified or updated frequently. Zero-copy cloning is also not suitable for scenarios where the cloned object needs to be shared across different accounts in different cloud regions. In these scenarios, copying of data would be required, either by using the COPY INTO command or by using data sharing with secure views3 The following are examples of development and testing scenarios where copying of data would be required, and zero-copy cloning would not be suitable:
Developers create their own datasets to work against transformed versions of the live data. This scenario requires copying of data because the developers need to modify the data or metadata of the cloned object to perform transformations, such as adding, deleting, or updating columns, rows, or values. Zero-copy cloning would not be suitable because it would create a read-only clone that shares the same data and metadata as the original object, and any changes made to the clone would affect the original object as well4 Data is in a production Snowflake account that needs to be provided to Developers in a separate development/testing Snowflake account in the same cloud region. This scenario requires copying of data because the data needs to be shared across different accounts in the same cloud region. Zero-copy cloning would not be suitable because it would create a clone within the same account as the original object, and it would not allow sharing the clone with another account. To share data across different accounts in the same cloud region, data sharing with secure views or COPY INTO command can be used5 The following are examples of development and testing scenarios where zero-copy cloning would be suitable, and copying of data would not be required:
Production and development run in different databases in the same account, and Developers need to see production-like data but with specific columns masked. This scenario can use zero-copy cloning because the data needs to be shared within the same account, and the cloned object does not need to have different data or metadata than the original object. Zero-copy cloning can create a clone of the production database in the development database, and the clone can have the same data and metadata as the original database. To mask specific columns, secure views can be created on top of the clone, and the developers can access the secure views instead of the clone directly6 Developers create their own copies of a standard test database previously created for them in the development account, for their initial development and unit testing. This scenario can use zero-copy cloning because the data needs to be shared within the same account, and the cloned object does not need to have different data or metadata than the original object. Zero-copy cloning can create a clone of the standard test database for each developer, and the clone can have the same data and metadata as the original database. The developers can use the clone for their initial development and unit testing, and any changes made to the clone would not affect the original database or other clones7 The release process requires pre-production testing of changes with data of production scale and complexity. For security reasons, pre-production also runs in the production account. This scenario can use zero-copy cloning because the data needs to be shared within the same account, and the cloned object does not need to have different data or metadata than the original object. Zero-copy cloning can create a clone of the production database in the pre-production database, and the clone can have the same data and metadata as the original database. The pre-production testing can use the clone to test the changes with data of production scale and complexity, and any changes made to the clone would not affect the original database or the production environment8 Reference:
1: SnowPro Advanced: Architect | Study Guide 9
2: Snowflake Documentation | Cloning Overview
3: Snowflake Documentation | Loading Data Using COPY into a Table
4: Snowflake Documentation | Transforming Data During a Load
5: Snowflake Documentation | Data Sharing Overview
6: Snowflake Documentation | Secure Views
7: Snowflake Documentation | Cloning Databases, Schemas, and Tables
8: Snowflake Documentation | Cloning for Testing and Development
: SnowPro Advanced: Architect | Study Guide
: Cloning Overview
: Loading Data Using COPY into a Table
: Transforming Data During a Load
: Data Sharing Overview
: Secure Views
: Cloning Databases, Schemas, and Tables
: Cloning for Testing and Development
NEW QUESTION # 220
An Architect is creating a new database role and is considering using the OR REPLACE keywords in the CREATE DATABASE ROLE command.
What should be considered before using OR REPLACE?
Answer: A
Explanation:
Using CREATE OR REPLACE DATABASE ROLE in Snowflake drops and recreates the role if it already exists. While this can simplify deployment scripts, it has important side effects that architects must understand. When a database role is dropped and recreated, all grants associated with that role-including grants to shares-are removed (Answer B). This can unintentionally break data sharing configurations or downstream access.
Although the role itself can be recreated, the loss of grants requires manual remediation, increasing operational risk. The OR REPLACE syntax is supported for database roles, and while privilege requirements matter, they are not the key risk being tested here.
For SnowPro Architect candidates, this question reinforces best practices around role lifecycle management and governance. In production environments, replacing roles should be done cautiously, with a clear understanding of grant dependencies and the potential impact on security and data sharing.
=========
NEW QUESTION # 221
An Architect is troubleshooting a query with poor performance using the QUERY_HIST0RY function. The Architect observes that the COMPILATIONJHME is greater than the EXECUTIONJTIME.
What is the reason for this?
Answer: B
Explanation:
Compilation time is the time it takes for the optimizer to create an optimal query plan for the efficient execution of the query. It also involves some pruning of partition files, making the query execution efficient2 If the compilation time is greater than the execution time, it means that the optimizer spent more time analyzing the query than actually running it. This could indicate that the query has overly complex logic, such as multiple joins, subqueries, aggregations, or expressions. The complexity of the query could also affect the size and quality of the query plan, which could impact the performance of the query3 To reduce the compilation time, the Architect can try to simplify the query logic, use views or common table expressions (CTEs) to break down the query into smaller parts, or use hints to guide the optimizer. The Architect can also use the EXPLAIN command to examine the query plan and identify potential bottlenecks or inefficiencies4 References:
* 1: SnowPro Advanced: Architect | Study Guide 5
* 2: Snowflake Documentation | Query Profile Overview 6
* 3: Understanding Why Compilation Time in Snowflake Can Be Higher than Execution Time 7
* 4: Snowflake Documentation | Optimizing Query Performance 8
* : SnowPro Advanced: Architect | Study Guide
* : Query Profile Overview
* : Understanding Why Compilation Time in Snowflake Can Be Higher than Execution Time
* : Optimizing Query Performance
NEW QUESTION # 222
An Architect needs to improve the performance of reports that pull data from multiple Snowflake tables, join, and then aggregate the data. Users access the reports using several dashboards. There are performance issues on Monday mornings between 9:00am-11:00am when many users check the sales reports.
The size of the group has increased from 4 to 8 users. Waiting times to refresh the dashboards has increased significantly. Currently this workload is being served by a virtual warehouse with the following parameters:
AUTO-RESUME = TRUE AUTO_SUSPEND = 60 SIZE = Medium
What is the MOST cost-effective way to increase the availability of the reports?
Answer: B
Explanation:
The most cost-effective way to increase the availability and performance of the reports during peak usage times, while keeping costs under control, is to use a multi-cluster warehouse in auto-scale mode. Option D suggests using a multi-cluster warehouse with 1 size Medium cluster and allowing it to auto-scale between 1 and 4 clusters based on demand. This setup ensures that additional computing resources are available when needed (e.g., during Monday morning peaks) and are scaled down to minimize costs when the demand decreases. This approach optimizes resource utilization and cost by adjusting the compute capacity dynamically, rather than maintaining a larger fixed size or multiple clusters continuously.
Reference: Snowflake's official documentation on managing warehouses and using auto-scaling features.
NEW QUESTION # 223
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