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Actual ADA-C01 Test Material Makes You More Efficient - PDF4Test
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Snowflake ADA-C01 Exam Syllabus Topics:| Topic | Details | | Topic 1 | - Snowflake Security, Role-Based Access Control (RBAC), and User Administration: This section of the exam measures the skills of Snowflake Administrators and Cloud Security Engineers and covers authentication, access control, and network management in Snowflake. Candidates must understand how to configure authentication methods such as SSO, MFA, OAuth, and key-pair authentication, and how to manage network policies and private connectivity. The domain also tests knowledge of user and role management using SCIM, designing access control architecture, and applying the RBAC framework to ensure secure user authorization and data protection within Snowflake environments.
| | Topic 2 | - Data Sharing, Data Exchange, and Snowflake Marketplace: This section of the exam measures the skills of Data Integration Specialists and Data Platform Administrators and covers managing and implementing data-sharing solutions within Snowflake. It evaluates understanding of data sharing models across regions and clouds, secure data sharing methods, and managing provider-consumer relationships. The domain also includes the use of Snowflake Data Exchange and Marketplace to publish, consume, and manage data listings, ensuring secure collaboration and efficient data monetization.
| | Topic 3 | - Performance Monitoring and Tuning: This section of the exam measures the skills of Cloud Infrastructure Engineers and Performance Analysts and focuses on optimizing Snowflake compute and storage resources. Candidates will need to understand how to configure and manage virtual warehouses, evaluate query profiles, and apply caching and clustering strategies for performance tuning. It also includes monitoring concurrency, resource utilization, and implementing cost optimization strategies. The ability to interpret, explain plans, apply search optimization, and manage cost controls is key for maintaining efficient Snowflake environments.
| | Topic 4 | - Disaster Recovery, Backup, and Data Replication: This section of the exam measures the skills of Disaster Recovery Engineers and Cloud Operations Managers and covers Snowflake methods for ensuring business continuity. Candidates must understand how to replicate databases and account-level objects, implement failover strategies, and perform backup and restoration through Time Travel and Fail-safe features. The domain emphasizes replication across accounts, handling data consistency during failover, and applying cost-efficient disaster recovery strategies to maintain availability during outages or regional failures.
| | Topic 5 | - Account Management and Data Governance: This section of the exam measures the skills of Data Governance Managers and Database Administrators and covers account organization, access control, and regulatory data protection. Candidates will learn how to manage organizational accounts, encryption keys, and Tri-Secret Secure implementations. It focuses on applying best practices in ORGADMIN and ACCOUNTADMIN roles, implementing masking and row access policies, and performing data classification and tagging. The domain also emphasizes data auditing, account identifiers, and effective management of tables, views, and query operations to support enterprise-wide governance standards.
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Snowflake SnowPro Advanced Administrator Sample Questions (Q26-Q31):NEW QUESTION # 26
Which Snowflake objects can be managed using SCIM integration? (Select TWO).
- A. Users
- B. Roles
- C. Stages
- D. Shares
- E. Warehouses
Answer: A,B
Explanation:
Explanation
A SCIM security integration allows the automated management of user identities and groups (i.e. roles) by creating an interface between Snowflake and a third-party Identity Provider (IdP)1. Snowflake supports SCIM integration with Okta, Azure, and custom SCIM clients2. SCIM integration does not support managing other Snowflake objects, such as stages, warehouses, or shares3. Therefore, the answer is B. Users and D. Roles.
NEW QUESTION # 27
A Snowflake Administrator is investigating why a query is not re-using the persisted result cache.
The Administrator found the two relevant queries from the SNOWFLAKE. ACCOUNT_USAGE. QUERY_HISTORY view:

Why is the second query re-scanning micro-partitions instead of using the first query's persisted result cache?
- A. The queries are executed with two different roles.
- B. The second query includes a CURRENT_DATE () function.
- C. The queries are executed with two different virtual warehouses.
- D. The second query includes a CURRENT_TIMESTAMP () function.
Answer: D
Explanation:
The inclusion of the CURRENT_TIMESTAMP() function in the second query prevents it from re-using the first query's persisted result cache because this function makes each execution unique due to the constantly changing timestamp. According to the Snowflake documentation, "The query does not include non-reusable functions, which return different results for successive runs of the same query. UUID_STRING, RANDOM, and RANDSTR are good examples of non-reusable functions." The CURRENT_TIMESTAMP() function is another example of a non-reusable function, as it returns the current date and time at the start of query execution, which varies for each run. Therefore, the second query is not identical to the first query, and the result cache is not reused. The other options are either incorrect or irrelevant to the question. Option B is incorrect, as the CURRENT_DATE() function is a reusable function, as it returns the same value for all queries executed within the same day. Option C is irrelevant, as the virtual warehouse used to execute the query does not affect the result cache reuse. Option D is also irrelevant, as the role used to execute the query does not affect the result cache reuse, as long as the role has the necessary access privileges for all the tables used in the query.
NEW QUESTION # 28
Which tasks can be performed by the ORGADMIN role? (Select THREE).
- A. View usage information for all accounts in the organization.
- B. Create a reader account to share data with another organization.
- C. View a list of all regions enabled for the organization.
- D. Create one or more accounts in the organization.
- E. Perform zero-copy cloning on account data.
- F. Create secure views on application tables within the organization.
Answer: A,C,D
Explanation:
Explanation
A user with the ORGADMIN role can perform the following tasks1:
*Create one or more accounts in the organization.
*View a list of all regions enabled for the organization.
*View usage information for all accounts in the organization.
Option C is incorrect because creating secure views on application tables is not a function of the ORGADMIN role, but rather a function of the roles that have access to the tables and schemas within the accounts. Option E is incorrect because performing zero-copy cloning on account data is not a function of the ORGADMIN role, but rather a function of the roles that have the CLONE privilege on the objects within the accounts. Option F is incorrect because creating a reader account to share data with another organization is not a function of the ORGADMIN role, but rather a function of the roles that have the CREATE SHARE privilege on the objects within the accounts.
NEW QUESTION # 29
A Snowflake Administrator has a multi-cluster virtual warehouse and is using the Snowflake Business Critical edition. The minimum number of clusters is set to 2 and the maximum number of clusters is set to 10. This configuration works well for the standard workload, rarely exceeding 5 running clusters. However, once a month the Administrator notes that there are a few complex long-running queries that are causing increased queue time and the warehouse reaches its maximum limit at 10 clusters.
Which solutions will address the issues happening once a month? (Select TWO).
- A. Have the group running the complex monthly queries use a separate appropriately-sized warehouse to support their workload.
- B. Examine the complex queries and determine if they can be made more efficient using clustering keys or materialized views.
- C. Increase the minimum number of clusters started in the multi-cluster configuration to 5.
- D. Use a task to increase the cluster size for the time period that the more complex queries are running and another task to reduce the size of the cluster once the complex queries complete.
- E. Increase the multi-cluster maximum to 20 or more clusters.
Answer: A,D
Explanation:
According to the Snowflake documentation1, a multi-cluster warehouse is a virtual warehouse that consists of multiple clusters of compute resources that can scale up or down automatically to handle the concurrency and performance needs of the queries submitted to the warehouse. A multi-cluster warehouse has a minimum and maximum number of clusters that can be specified by the administrator. Option A is a possible solution to address the issues happening once a month, as it allows the administrator to use a task to increase the cluster size for the time period that the more complex queries are running and another task to reduce the size of the cluster once the complex queries complete. This way, the warehouse can have more resources available to handle the complex queries without reaching the maximum limit of 10 clusters, and then return to the normal cluster size to save costs. Option B is another possible solution to address the issues happening once a month, as it allows the administrator to have the group running the complex monthly queries use a separate appropriately-sized warehouse to support their workload. This way, the warehouse can isolate the complex queries from the standard workload and avoid queue time and resource contention. Option C is not a recommended solution to address the issues happening once a month, as it would increase the costs and complexity of managing the multi-cluster warehouse, and may not solve the underlying problem of inefficient queries. Option D is a good practice to improve the performance of the queries, but it is not a direct solution to address the issues happening once a month, as it requires analyzing and optimizing the complex queries using clustering keys or materialized views, which may not be feasible or effective in all cases. Option E is not a recommended solution to address the issues happening once a month, as it would increase the costs and waste resources by starting more clusters than needed for the standard workload.
NEW QUESTION # 30
A company has many users in the role ANALYST who routinely query Snowflake through a reporting tool.
The Administrator has noticed that the ANALYST users keep two
small clusters busy all of the time, and occasionally they need three or four clusters of that size.
Based on this scenario, how should the Administrator set up a virtual warehouse to MOST efficiently support this group of users?
- A. Create a multi-cluster warehouse with MIN_CLUSTERS set to 2. Set the warehouse to auto-resume and auto-suspend, and give USAGE privileges to the ANALYST role. Allow the warehouse to auto-scale.
- B. Create a standard X-Large warehouse, which is equivalent to four small clusters. Set the warehouse to auto-resume and auto-suspend, and give USAGE privileges to the ANALYST role.
- C. Create a multi-cluster warehouse with MIN_CLUSTERS set to 1. Give MANAGE privileges to the ANALYST role so this group can start and stop the warehouse, and increase the number of clusters as needed.
- D. Create four virtual warehouses (sized Small through XL) and set them to auto-suspend and auto-resume.Have users in the ANALYST role select the appropriate warehouse based on how many queries are being run.
Answer: A
Explanation:
Explanation
According to the Snowflake documentation1, a multi-cluster warehouse is a virtual warehouse that consists of multiple clusters of compute resources that can scale up or down automatically to handle the concurrency and performance needs of the queries submitted to the warehouse. A multi-cluster warehouse has a minimum and maximum number of clusters that can be specified by the administrator. Option B is the most efficient way to support the group of users, as it allows the administrator to create a multi-cluster warehouse with MIN_CLUSTERS set to 2, which means that the warehouse will always have two clusters running to handle the standard workload. The warehouse can also auto-scale up to the maximum number of clusters (which can be set according to the peak workload) when there is a spike in demand, and then scale down when the demand decreases. The warehouse can also auto-resume and auto-suspend, which means that the warehouse will automatically start when a query is submitted and automatically stop after a period of inactivity. The administrator can also give USAGE privileges to the ANALYST role, which means that the users can use the warehouse to execute queries and load data, but not modify or operate the warehouse. Option A is not efficient, as it requires the users to manually start and stop the warehouse, and increase the number of clusters as needed, which can be time-consuming and error-prone. Option C is not efficient, as it creates a standard X-Large warehouse, which is equivalent to four small clusters, which may be more than needed for the standard workload, and may not be enough for the peak workload. Option D is not efficient, as it creates four virtual warehouses of different sizes, which can be confusing and cumbersome for the users to select the appropriate warehouse based on how many queries are being run, and may also result in wasted resources and costs.
NEW QUESTION # 31
......
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