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Snowflake SnowPro Advanced Architect Certification Sample Questions (Q116-Q121):

NEW QUESTION # 116
Company A has recently acquired company B. The Snowflake deployment for company B is located in the Azure West Europe region.
As part of the integration process, an Architect has been asked to consolidate company B's sales data into company A's Snowflake account which is located in the AWS us-east-1 region.
How can this requirement be met?

A. Build a custom data pipeline using Azure Data Factory or a similar tool to extract the sales data from company B's Snowflake account. Transform the data, then load it into company A's Snowflake account.
B. Replicate the sales data from company B's Snowflake account into company A's Snowflake account using cross-region data replication within Snowflake. Configure a direct share from company B's account to company A's account.
C. Export the sales data from company B's Snowflake account as CSV files, and transfer the files to company A's Snowflake account. Import the data using Snowflake's data loading capabilities.
D. Migrate company B's Snowflake deployment to the same region as company A's Snowflake deployment, ensuring data locality. Then perform a direct database-to-database merge of the sales data.

Answer: B

Explanation:
The best way to meet the requirement of consolidating company B's sales data into company A's Snowflake account is to use cross-region data replication within Snowflake. This feature allows data providers to securely share data with data consumers across different regions and cloud platforms. By replicating the sales data from company B's account in Azure West Europe region to company A's account in AWS us-east-1 region, the data will be synchronized and available for consumption. To enable data replication, the accounts must be linked and replication must be enabled by a user with the ORGADMIN role. Then, a replication group must be created and the sales database must be added to the group. Finally, a direct share must be configured from company B's account to company A's account to grant access to the replicated data. This option is more efficient and secure than exporting and importing data using CSV files or migrating the entire Snowflake deployment to another region or cloud platform. It also does not require building a custom data pipeline using external tools.
References:
* Sharing data securely across regions and cloud platforms
* Introduction to replication and failover
* Replication considerations
* Replicating account objects

NEW QUESTION # 117
What is a characteristic of Role-Based Access Control (RBAC) as used in Snowflake?

A. Privileges can be granted at the database level and can be inherited by all underlying objects.
B. A user can use a "super-user" access along with securityadmin to bypass authorization checks and access all databases, schemas, and underlying objects.
C. A user can create managed access schemas to support current and future grants and ensure only object owners can grant privileges to other roles.
D. A user can create managed access schemas to support future grants and ensure only schema owners can grant privileges to other roles.

Answer: A

NEW QUESTION # 118
Consider the following scenario where a masking policy is applied on the CREDICARDND column of the CREDITCARDINFO table. The masking policy definition Is as follows:

Sample data for the CREDITCARDINFO table is as follows:
NAME EXPIRYDATE CREDITCARDNO
JOHN DOE 2022-07-23 4321 5678 9012 1234
if the Snowflake system rotes have not been granted any additional roles, what will be the result?

A. The sysadmin can see the CREDICARDND column data in clear text.
B. Anyone with the Pl_ANALYTICS role will see the last 4 characters of the CREDICARDND column data in dear text.
C. The owner of the table will see the CREDICARDND column data in clear text.
D. Anyone with the Pl_ANALYTICS role will see the CREDICARDND column as*** 'MASKED* **'.

Answer: D

Explanation:
The masking policy defined in the image indicates that if a user has the PI_ANALYTICS role, they will be able to see the last 4 characters of the CREDITCARDNO column data in clear text. Otherwise, they will see 'MASKED'. Since Snowflake system roles have not been granted any additional roles, they won't have the PI_ANALYTICS role and therefore cannot view the last 4 characters of credit card numbers.
To apply a masking policy on a column in Snowflake, you need to use the ALTER TABLE ... ALTER COLUMN command or the ALTER VIEW command and specify the policy name. For example, to apply the creditcardno_mask policy on the CREDITCARDNO column of the CREDITCARDINFO table, you can use the following command:
ALTER TABLE CREDITCARDINFO ALTER COLUMN CREDITCARDNO SET MASKING POLICY creditcardno_mask; For more information on how to create and use masking policies in Snowflake, you can refer to the following resources:
CREATE MASKING POLICY: This document explains the syntax and usage of the CREATE MASKING POLICY command, which allows you to create a new masking policy or replace an existing one.
Using Dynamic Data Masking: This guide provides instructions on how to configure and use dynamic data masking in Snowflake, which is a feature that allows you to mask sensitive data based on the execution context of the user.
ALTER MASKING POLICY: This document explains the syntax and usage of the ALTER MASKING POLICY command, which allows you to modify the properties of an existing masking policy.

NEW QUESTION # 119
Two queries are run on the customer_address table:
create or replace TABLE CUSTOMER_ADDRESS ( CA_ADDRESS_SK NUMBER(38,0),
CA_ADDRESS_ID VARCHAR(16), CA_STREET_NUMBER VARCHAR(IO) CA_STREET_NAME
VARCHAR(60), CA_STREET_TYPE VARCHAR(15), CA_SUITE_NUMBER VARCHAR(10), CA_CITY VARCHAR(60), CA_COUNTY VARCHAR(30), CA_STATE VARCHAR(2), CA_ZIP VARCHAR(10), CA_COUNTRY VARCHAR(20), CA_GMT_OFFSET NUMBER(5,2), CA_LOCATION_TYPE VARCHAR(20) ); ALTER TABLE DEMO_DB.DEMO_SCH.CUSTOMER_ADDRESS ADD SEARCH OPTIMIZATION ON SUBSTRING(CA_ADDRESS_ID); Which queries will benefit from the use of the search optimization service? (Select TWO).

A. select*fromDEMO_DB.DEMO_SCH.CUSTOMER_ADDRESSWhereCA_ADDRESS_IDLIKE
'%BAAASKD%';
B. select * from DEMO_DB.DEMO_SCH.CUSTOMER_ADDRESS Where CA_ADDRESS_ID= substring('AAAAAAAAPHPPLBAAASKDJHASLKDJHASKJD',1,16);
C. select*fromDEMO_DB.DEMO_SCH.CUSTOMER_ADDRESSWhereCA_ADDRESS_IDNOT LIKE
'%AAAAAAAAPHPPL%';
D. select * from DEMO_DB.DEMO_SCH.CUSTOMER_ADDRESS Where
substring(CA_ADDRESS_ID,1,8)=
substring('AAAAAAAAPHPPLBAAASKDJHASLKDJHASKJD',1,8);
E. select*fromDEMO_DB.DEMO_SCH.CUSTOMER_ADDRESSWhereCA_ADDRESS_IDLIKE
'%PHPP%';

Answer: B,D

Explanation:
The use of the search optimization service in Snowflake is particularly effective when queries involve operations that match exact substrings or start from the beginning of a string. The ALTER TABLE command adding search optimization specifically for substrings on the CA_ADDRESS_ID field allows the service to create an optimized search path for queries using substring matches.
* Option A benefits because it directly matches a substring from the start of the CA_ADDRESS_ID, aligning with the optimization's capability to quickly locate records based on the beginning segments of strings.
* Option B also benefits, despite performing a full equality check, because it essentially compares the full length of CA_ADDRESS_ID to a substring, which can leverage the substring index for efficient
* retrieval.Options C, D, and E involve patterns that do not start from the beginning of the string or use negations, which are not optimized by the search optimization service configured for starting substring matches.References: Snowflake's documentation on the use of search optimization for substring matching in SQL queries.

NEW QUESTION # 120
An Architect needs to design a data unloading strategy for Snowflake, that will be used with the COPY INTO
<location> command.
Which configuration is valid?

A. Location of files: Azure ADLS
. File formats: JSON, XML, Avro, Parquet, ORC
. Compression: bzip2
. Encryption: User-supplied key
B. Location of files: Snowflake internal location
. File formats: CSV, XML
. File encoding: UTF-8
. Encryption: 128-bit
C. Location of files: Amazon S3
. File formats: CSV, JSON
. File encoding: Latin-1 (ISO-8859)
. Encryption: 128-bit
D. Location of files: Google Cloud Storage
. File formats: Parquet
. File encoding: UTF-8
Compression: gzip

Answer: D

NEW QUESTION # 121
......

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