Updated ADA-C01 Exam Questions: SnowPro Advanced Administrator are the most veracious Preparation Dumps - RealValidExam

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In recent, RealValidExam began to provide you with the latest exam dumps about IT certification test, such as Snowflake ADA-C01 Certification Dumps are developed based on the latest IT certification exam. RealValidExam Snowflake ADA-C01 certification training dumps will tell you the latest news about the exam. The changes of the exam outline and those new questions that may appear are included in our dumps. So if you want to attend IT certification exam, you'd better make the best of RealValidExam questions and answers. Only in this way can you prepare well for the exam.

Snowflake ADA-C01 Exam Syllabus Topics:

Topic	Details
Topic 1	Snowflake Security, Role-Based Access Control (RBAC), and User Administration Disaster Recovery, Backup, and Data Replication
Topic 2	Given a scenario, manage databases, tables, and views Manage organizations and access control
Topic 3	Given a scenario, create and manage access control Given a scenario, implement resource monitors
Topic 4	Interpret and make recommendations for data clustering Manage DML locking and concurrency in Snowflake
Topic 5	Given a scenario, configure access controls Set up and manage security administration and authorization

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Snowflake SnowPro Advanced Administrator Sample Questions (Q59-Q64):

NEW QUESTION # 59
What are characteristics of Dynamic Data Masking? (Select TWO).

A. A single masking policy can be applied to columns with different data types.
B. A single masking policy can be applied to columns in different tables.
C. A masking policy that is currently set on a table can be dropped.
D. The role that creates the masking policy will always see unmasked data in query results.
E. A masking policy can be applied to the VALUE column of an external table.

Answer: A,B

Explanation:
According to the Using Dynamic Data Masking documentation, Dynamic Data Masking is a feature that allows you to alter sections of data in table and view columns at query time using a predefined masking strategy. The following are some of the characteristics of Dynamic Data Masking:
* A single masking policy can be applied to columns in different tables. This means that you can write a policy once and have it apply to thousands of columns across databases and schemas.
* A single masking policy can be applied to columns with different data types. This means that you can use the same masking strategy for columns that store different kinds of data, such as strings, numbers, dates, etc.
* A masking policy that is currently set on a table can be dropped. This means that you can remove the masking policy from the table and restore the original data visibility.
* A masking policy can be applied to the VALUE column of an external table. This means that you can mask data that is stored in an external stage and queried through an external table.
* The role that creates the masking policy will always see unmasked data in query results. This is not true, as the masking policy can also apply to the creator role depending on the execution context conditions defined in the policy. For example, if the policy specifies that only users with a certain custom entitlement can see the unmasked data, then the creator role will also need to have that entitlement to see the unmasked data.

NEW QUESTION # 60
For Snowflake network policies, what will occur when the account_level and user_level network policies are both defined?

A. A network policy error will be generated with no definitions provided.
B. The user_level network policies will not be supported.
C. The user_level policy will override the account_level policy.
D. The account_level policy will override the user_level policy.

Answer: C

Explanation:
Explanation
According to the Network Policies documentation, a network policy can be applied to an account, a security integration, or a user. If there are network policies applied to more than one of these, the most specific network policy overrides more general network policies. The following summarizes the order of precedence:
*Account: Network policies applied to an account are the most general network policies. They are overridden by network policies applied to a security integration or user.
*Security Integration: Network policies applied to a security integration override network policies applied to the account, but are overridden by a network policy applied to a user.
*User: Network policies applied to a user are the most specific network policies. They override both accounts and security integrations.
Therefore, if both the account_level and user_level network policies are defined, the user_level policy will take effect and the account_level policy will be ignored. The other options are incorrect because:
*The account_level policy will not override the user_level policy, as explained above.
*The user_level network policies will be supported, as they are part of the network policyfeature.
*A network policy error will not be generated, as there is no conflict between the account_level and user_level network policies.

NEW QUESTION # 61
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 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.
B. 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.
C. 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.
D. 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.

Answer: D

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 # 62
Review the output of the SHOW statement below which displays the current grants on the table DB1. S1. T1:

This statement is executed:
USE ROLE ACCOUNTADMIN;
DROP ROLE A;
What will occur?

A. The SELECT privilege on table DB1. S1. T1 to role B will be shown as GRANTED_BY the role ACCOUNTADMIN.
B. The OWNERSHIP privilege on table DB1. S1. T1 will be transferred to the ACCOUNTADMIN role.
C. The table object DB1. S1. T1 will be dropped.
D. The SELECT privileges for roles B and C will remain.

Answer: D

Explanation:
Explanation
Dropping role A does not affect the SELECT privileges granted to roles B and C on the table DB1.S1.T1.
According to the Snowflake documentation, dropping a role revokes all privileges granted to the role, but does not revoke any privileges granted by the role. Therefore, the OWNERSHIP privilege on the table DB1.S1.T1 will be revoked from role A, but the SELECT privileges granted by role A to role B and by role B to role C will remain. The GRANTED_BY column will still show the original grantor of the privilege, not the ACCOUNTADMIN role.

NEW QUESTION # 63
In which scenario will use of an external table simplify a data pipeline?

A. When continuously writing data from a Snowflake table to external storage
B. When accessing a Snowflake table from an external database within the same region
C. When accessing a Snowflake table that references data files located in cloud storage
D. When accessing a Snowflake table from a relational database

Answer: C

Explanation:
According to the Introduction to External Tables documentation, an external table is a Snowflake feature that allows you to query data stored in an external stage as if the data were inside a table in Snowflake. The external stage is not part of Snowflake, so Snowflake does not store or manage the stage. This simplifies the data pipeline by eliminating the need to load the data into Snowflake before querying it. External tables can access data stored in any format that the COPY INTO <table> command supports, such as CSV, JSON, AVRO, ORC, or PARQUET. The other scenarios do not involve external tables, but rather require data loading, unloading, or federation.

NEW QUESTION # 64
......

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UPDATED ADA-C01 EXAM QUESTIONS: SNOWPRO ADVANCED ADMINISTRATOR ARE THE MOST VERACIOUS PREPARATION DUMPS - REALVALIDEXAM

Updated ADA-C01 Exam Questions: SnowPro Advanced Administrator are the most veracious Preparation Dumps - RealValidExam