EXAM SNOWFLAKE ADA-C01 SAMPLE & RELIABLE ADA-C01 BRAINDUMPS PPT

Exam Snowflake ADA-C01 Sample & Reliable ADA-C01 Braindumps Ppt

Exam Snowflake ADA-C01 Sample & Reliable ADA-C01 Braindumps Ppt

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Tags: Exam ADA-C01 Sample, Reliable ADA-C01 Braindumps Ppt, Real ADA-C01 Exam Dumps, ADA-C01 Interactive Questions, Latest ADA-C01 Exam Practice

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Snowflake ADA-C01 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Given a scenario, configure access controls
  • Set up and manage security administration and authorization
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
  • Set up and manage network and private connectivity
  • Given a scenario, manage Snowflake Time Travel and Fail-safe
Topic 5
  • Snowflake Security, Role-Based Access Control (RBAC), and User Administration
  • Disaster Recovery, Backup, and Data Replication
Topic 6
  • Implement and manage data governance in Snowflake
  • Data Sharing, Data Exchange, and Snowflake Marketplace
Topic 7
  • Manage and implement data sharing
  • Given a set of business requirements, establish access control architecture

>> Exam Snowflake ADA-C01 Sample <<

2025 Efficient ADA-C01 – 100% Free Exam Sample | Reliable ADA-C01 Braindumps Ppt

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Snowflake SnowPro Advanced Administrator Sample Questions (Q47-Q52):

NEW QUESTION # 47
What are characteristics of Dynamic Data Masking? (Select TWO).

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

Answer: A,E

Explanation:
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 # 48
An Administrator loads data into a staging table every day. Once loaded, users from several different departments perform transformations on the data and load it into different production tables.
How should the staging table be created and used to MINIMIZE storage costs and MAXIMIZE performance?

  • A. Create it as a permanent table with a retention time of 0 days.
  • B. Create it as a transient table with a retention time of 0 days.
  • C. Create it as a temporary table with a retention time of 0 days.
  • D. Create it as an external table, which will not incur Time Travel costs.

Answer: B

Explanation:
Explanation
According to the Snowflake documentation1, a transient table is a type of table that does not support Time Travel or Fail-safe, which means that it does not incur any storage costs for maintaining historical versions of the data or backups for disaster recovery. A transient table can be dropped at any time, and the data is not recoverable. A transient table can also have a retention time of 0 days, which means that the data is deleted immediately after the table is dropped or truncated. Therefore, creating the staging table as a transient table with a retention time of 0 days can minimize the storage costs and maximize the performance, as the data is only loaded and transformed once, and then deleted after the production tables are populated. Option A is incorrect because creating the staging table as an external table, which references data files stored in a cloud storage location, can incur additional costs and complexity for data transfer and synchronization, and may not provide the best performance for data loading and transformation. Option C is incorrect because creating the staging table as a temporary table, which is automatically dropped when the session ends or the user logs out, can cause data loss or inconsistency if the session is interrupted or terminated before the production tables are populated. Option D is incorrect because creating the staging table as a permanent table, which supports Time Travel and Fail-safe, can incur additional storage costs for maintaining historical versions of the data and backups for disaster recovery, and may not provide the best performance for data loading and transformation.


NEW QUESTION # 49
A retailer uses a TRANSACTIONS table (100M rows, 1.2 TB) that has been clustered by the STORE_ID column (varchar(50)). The vast majority of analyses on this table are grouped by STORE_ID to look at store performance.
There are 1000 stores operated by the retailer but most sales come from only 20 stores. The Administrator notes that most queries are currently experiencing poor pruning, with large amounts of bytes processed by even simple queries.
Why is this occurring?

  • A. The cardinality of the stores to transaction count ratio is too low to use the STORE_ID as a clustering key.
  • B. The STORE_ID should be numeric.
  • C. The table is not big enough to take advantage of the clustering key.
  • D. Sales across stores are not uniformly distributed.

Answer: D

Explanation:
Explanation
According to the Snowflake documentation1, clustering keys are most effective when the data is evenly distributed across the key values. If the data is skewed, such as in this case where most sales come from only
20 stores out of 1000, then the micro-partitions will not be well-clustered and the pruning will be poor. This means that more bytes will be scanned by queries, even if they filter by STORE_ID. Option A is incorrect because the data type of the clustering key does not affect the pruning. Option B is incorrect because the table is large enough to benefit from clustering, if the data was more balanced. Option D is incorrect because the cardinality of the clustering key is not relevant for pruning, as long as the key values are distinct.
1: Considerations for Choosing Clustering for a Table | Snowflake Documentation


NEW QUESTION # 50
A Snowflake organization MYORG consists of two Snowflake accounts:

The ACCOUNT1 has a database PROD_DB and the ORGADMIN role enabled.
Management wants to have the PROD_DB database replicated to ACCOUNT2.
Are there any necessary configuration steps in ACCOUNT1 before the database replication can be configured and initiated in ACCOUNT2?

  • A. It is not possible to replicate a database from an Enterprise edition Snowflake account to a Standard edition Snowflake account.
  • B. USE ROLE ORGADMIN;
    SELECT SYSTEMSGLOBAL_ACCOUNT_SET_PARAMETER ('MYORG. ACCOUNT1',
    'ENABLE_ACCOUNT_DATABASE_REPLICATION', 'TRUE');
    SELECT SYSTEMSGLOBAL_ACCOUNT_SET_PARAMETER ('MYORG. ACCOUNT2',
    'ENABLE_ACCOUNT_DATABASE_REPLICATION', 'TRUE');
    USE ROLE ACCOUNTADMIN;
    ALTER DATABASE PROD DB ENABLE REPLICATION TO ACCOUNTS MYORG. ACCOUNT2;
  • C. No configuration steps are necessary in ACCOUNT1. Replicating databases across accounts within the same Snowflake organization is enabled by default.
  • D. USE ROLE ORGADMIN;
    SELECT SYSTEMSGLOBAL ACCOUNT SET_PARAMETER ( 'MYORG. ACCOUNT1',
    'ENABLE_ACCOUNT_DATABASE_REPLICATION', 'TRUE');
    USE ROLE ACCOUNTADMIN;
    ALTER DATABASE PROD_DB ENABLE REPLICATION TO ACCOUNTS MYORG. ACCOUNT2
    IGNORE EDITION CHECK;

Answer: D

Explanation:
Explanation
According to the Snowflake documentation1, database replication across accounts within the same organization requires the following steps:
*Link the accounts in the organization using the ORGADMIN role.
*Enable account database replication for both the source and target accounts using the SYSTEM$GLOBAL_ACCOUNT_SET_PARAMETER function.
*Promote a local database to serve as the primary database and enable replication to the target accounts using the ALTER DATABASE ... ENABLE REPLICATION TO ACCOUNTS command.
*Create a secondary database in the target account using the CREATE DATABASE ... FROM SHARE command.
*Refresh the secondary database periodically using the ALTER DATABASE ... REFRESH command.
Option A is incorrect because it does not include the step of creating a secondary database in the target account. Option C is incorrect because replicating databases across accounts within the same organization is not enabled by default, but requires enabling account database replication for both the source and target accounts. Option D is incorrect because it is possible to replicate a database from an Enterprise edition Snowflake account to a Standard edition Snowflake account, as long as the IGNORE EDITION CHECK option is used in the ALTER DATABASE ... ENABLE REPLICATION TO ACCOUNTS command2.
Option B is correct because it includes all the necessary configuration steps in ACCOUNT1, except for creating a secondary database in ACCOUNT2, which can be done after the replication is enabled.


NEW QUESTION # 51
What session parameter can be used to test the integrity of secure views based on the account that is accessing that view?

  • A. PRODUCER_TEST_ACCT
  • B. SIMULATED_DATA_SHARING_CONSUMER
  • C. MIMIC_CONSUMER_ACCOUNT
  • D. TEST_ACCOUNT_ID

Answer: B

Explanation:
The SIMULATED_DATA_SHARING_CONSUMER session parameter allows a data provider to test the integrity of secure views based on the account that is accessing that view2. By setting this parameter to the name of the consumer account, the data provider can query the secure view and see the results that a user in the consumer account will see2. This helps to ensure that sensitive data in a shared database is not exposed to unauthorized users1. The other options are not valid session parameters in Snowflake3


NEW QUESTION # 52
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