[Q47-Q67] ARA-R01 Actual Questions - Instant Download Tests Free Updated Today!

QUESTION 47
A company is using Snowflake in Azure in the Netherlands. The company analyst team also has data in JSON format that is stored in an Amazon S3 bucket in the AWS Singapore region that the team wants to analyze.
The Architect has been given the following requirements:
1. Provide access to frequently changing data
2. Keep egress costs to a minimum
3. Maintain low latency
How can these requirements be met with the LEAST amount of operational overhead?

Use a materialized view on top of an external table against the S3 bucket in AWS Singapore.

Use an external table against the S3 bucket in AWS Singapore and copy the data into transient tables.

Copy the data between providers from S3 to Azure Blob storage to collocate, then use Snowpipe for data ingestion.

Use AWS Transfer Family to replicate data between the S3 bucket in AWS Singapore and an Azure Netherlands Blob storage, then use an external table against the Blob storage.

Option A is the best design to meet the requirements because it uses a materialized view on top of an external table against the S3 bucket in AWS Singapore. A materialized view is a database object that contains the results of a query and can be refreshed periodically to reflect changes in the underlying data1. An external table is a table that references data files stored in a cloud storage service, such as Amazon S32. By using a materialized view on top of an external table, the company can provide access to frequently changing data, keep egress costs to a minimum, and maintain low latency. This is because the materialized view will cache the query results in Snowflake, reducing the need to access the external data files and incur network charges.
The materialized view will also improve the query performance by avoiding scanning the external data files every time. The materialized view can be refreshed on a schedule or on demand to capture the changes in the external data files1.
Option B is not the best design because it uses an external table against the S3 bucket in AWS Singapore and copies the data into transient tables. A transient table is a table that is not subject to the Time Travel and Fail-safe features of Snowflake, and is automatically purged after a period of time3. By using an external table and copying the data into transient tables, the company will incur more egress costs and operational overhead than using a materialized view. This is because the external table will access the external data files every time a query is executed, and the copy operation will also transfer data from S3 to Snowflake. The transient tables will also consume more storage space in Snowflake and require manual maintenance to ensure they are up to date.
Option C is not the best design because it copies the data between providers from S3 to Azure Blob storage to collocate, then uses Snowpipe for data ingestion. Snowpipe is a service that automates the loading of data from external sources into Snowflake tables4. By copying the data between providers, the company will incur high egress costs and latency, as well as operational complexity and maintenance of the infrastructure. Snowpipe will also add another layer of processing and storage in Snowflake, which may not be necessary if the external data files are already in a queryable format.
Option D is not the best design because it uses AWS Transfer Family to replicate data between the S3 bucket in AWS Singapore and an Azure Netherlands Blob storage, then uses an external table against the Blob storage. AWS Transfer Family is a service that enables secure and seamless transfer of files over SFTP, FTPS, and FTP to and from Amazon S3 or Amazon EFS5. By using AWS Transfer Family, the company will incur high egress costs and latency, as well as operational complexity and maintenance of the infrastructure. The external table will also access the external data files every time a query is executed, which may affect the query performance.
References: 1: Materialized Views 2: External Tables 3: Transient Tables 4: Snowpipe Overview 5: AWS Transfer Family

QUESTION 48
A company has a table with that has corrupted data, named Data. The company wants to recover the data as it was 5 minutes ago using cloning and Time Travel.
What command will accomplish this?

CREATE CLONE TABLE Recover_Data FROM Data AT(OFFSET => -60*5);

CREATE CLONE Recover_Data FROM Data AT(OFFSET => -60*5);

CREATE TABLE Recover_Data CLONE Data AT(OFFSET => -60*5);

CREATE TABLE Recover Data CLONE Data AT(TIME => -60*5);

QUESTION 49
A table for IOT devices that measures water usage is created. The table quickly becomes large and contains more than 2 billion rows.

The general query patterns for the table are:
1. DeviceId, lOT_timestamp and Customerld are frequently used in the filter predicate for the select statement
2. The columns City and DeviceManuf acturer are often retrieved
3. There is often a count on Uniqueld
Which field(s) should be used for the clustering key?

lOT_timestamp

City and DeviceManuf acturer

Deviceld and Customerld

Uniqueld

QUESTION 50
At which object type level can the APPLY MASKING POLICY, APPLY ROW ACCESS POLICY and APPLY SESSION POLICY privileges be granted?

Global

Database

Schema

Table

QUESTION 51
Which technique will efficiently ingest and consume semi-structured data for Snowflake data lake workloads?

IDEF1X

Schema-on-write

Schema-on-read

Information schema

QUESTION 52
Which Snowflake data modeling approach is designed for BI queries?

3 NF

Star schema

Data Vault

Snowflake schema

QUESTION 53
How does a standard virtual warehouse policy work in Snowflake?

It conserves credits by keeping running clusters fully loaded rather than starting additional clusters.

It starts only if the system estimates that there is a query load that will keep the cluster busy for at least 6 minutes.

It starts only f the system estimates that there is a query load that will keep the cluster busy for at least 2 minutes.

It prevents or minimizes queuing by starting additional clusters instead of conserving credits.

QUESTION 54
How can an Architect enable optimal clustering to enhance performance for different access paths on a given table?

Create multiple clustering keys for a table.

Create multiple materialized views with different cluster keys.

Create super projections that will automatically create clustering.

Create a clustering key that contains all columns used in the access paths.

QUESTION 55
A Snowflake Architect is designing an application and tenancy strategy for an organization where strong legal isolation rules as well as multi-tenancy are requirements.
Which approach will meet these requirements if Role-Based Access Policies (RBAC) is a viable option for isolating tenants?

Create accounts for each tenant in the Snowflake organization.

Create an object for each tenant strategy if row level security is viable for isolating tenants.

Create an object for each tenant strategy if row level security is not viable for isolating tenants.

Create a multi-tenant table strategy if row level security is not viable for isolating tenants.

QUESTION 56
What built-in Snowflake features make use of the change tracking metadata for a table? (Choose two.)

The MERGE command

The UPSERT command

The CHANGES clause

A STREAM object

The CHANGE_DATA_CAPTURE command

QUESTION 57
A company is using a Snowflake account in Azure. The account has SAML SSO set up using ADFS as a SCIM identity provider. To validate Private Link connectivity, an Architect performed the following steps:
* Confirmed Private Link URLs are working by logging in with a username/password account
* Verified DNS resolution by running nslookups against Private Link URLs
* Validated connectivity using SnowCD
* Disabled public access using a network policy set to use the company’s IP address range However, the following error message is received when using SSO to log into the company account:
IP XX.XXX.XX.XX is not allowed to access snowflake. Contact your local security administrator.
What steps should the Architect take to resolve this error and ensure that the account is accessed using only Private Link? (Choose two.)

Alter the Azure security integration to use the Private Link URLs.

Add the IP address in the error message to the allowed list in the network policy.

Generate a new SCIM access token using system$generate_scim_access_token and save it to Azure AD.

Update the configuration of the Azure AD SSO to use the Private Link URLs.

Open a case with Snowflake Support to authorize the Private Link URLs’ access to the account.

QUESTION 58
An Architect entered the following commands in sequence:

USER1 cannot find the table.
Which of the following commands does the Architect need to run for USER1 to find the tables using the Principle of Least Privilege? (Choose two.)

GRANT ROLE PUBLIC TO ROLE INTERN;

GRANT USAGE ON DATABASE SANDBOX TO ROLE INTERN;

GRANT USAGE ON SCHEMA SANDBOX.PUBLIC TO ROLE INTERN;

GRANT OWNERSHIP ON DATABASE SANDBOX TO USER INTERN;

GRANT ALL PRIVILEGES ON DATABASE SANDBOX TO ROLE INTERN;

QUESTION 59
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?

The sysadmin can see the CREDICARDND column data in clear text.

The owner of the table will see the CREDICARDND column data in clear text.

Anyone with the Pl_ANALYTICS role will see the last 4 characters of the CREDICARDND column data in dear text.

Anyone with the Pl_ANALYTICS role will see the CREDICARDND column as*** ‘MASKED* **’.

QUESTION 60
How do Snowflake databases that are created from shares differ from standard databases that are not created from shares? (Choose three.)

Shared databases are read-only.

Shared databases must be refreshed in order for new data to be visible.

Shared databases cannot be cloned.

Shared databases are not supported by Time Travel.

Shared databases will have the PUBLIC or INFORMATION_SCHEMA schemas without explicitly granting these schemas to the share.

Shared databases can also be created as transient databases.

According to the SnowPro Advanced: Architect documents and learning resources, the ways that Snowflake databases that are created from shares differ from standard databases that are not created from shares are:
Shared databases are read-only. This means that the data consumers who access the shared databases cannot modify or delete the data or the objects in the databases. The data providers who share the databases have full control over the data and the objects, and can grant or revoke privileges on them1.
Shared databases cannot be cloned. This means that the data consumers who access the shared databases cannot create a copy of the databases or the objects in the databases. The data providers who share the databases can clone the databases or the objects, but the clones are not automatically shared2.
Shared databases are not supported by Time Travel. This means that the data consumers who access the shared databases cannot use the AS OF clause to query historical data or restore deleted data. The data providers who share the databases can use Time Travel on the databases or the objects, but the historical data is not visible to the data consumers3.
The other options are incorrect because they are not ways that Snowflake databases that are created from shares differ from standard databases that are not created from shares. Option B is incorrect because shared databases do not need to be refreshed in order for new data to be visible. The data consumers who access the shared databases can see the latest data as soon as the data providers update the data1. Option E is incorrect because shared databases will not have the PUBLIC or INFORMATION_SCHEMA schemas without explicitly granting these schemas to the share. The data consumers who access the shared databases can only see the objects that the data providers grant to the share, and the PUBLIC and INFORMATION_SCHEMA schemas are not granted by default4. Option F is incorrect because shared databases cannot be created as transient databases. Transient databases are databases that do not support Time Travel or Fail-safe, and can be dropped without affecting the retention period of the data. Shared databases are always created as permanent databases, regardless of the type of the source database5. References: Introduction to Secure Data Sharing | Snowflake Documentation, Cloning Objects | Snowflake Documentation, Time Travel | Snowflake Documentation, Working with Shares | Snowflake Documentation, CREATE DATABASE | Snowflake Documentation

QUESTION 61
Data is being imported and stored as JSON in a VARIANT column. Query performance was fine, but most recently, poor query performance has been reported.
What could be causing this?

There were JSON nulls in the recent data imports.

The order of the keys in the JSON was changed.

The recent data imports contained fewer fields than usual.

There were variations in string lengths for the JSON values in the recent dataimports.

Data is being imported and stored as JSON in a VARIANT column. Query performance was fine, but most recently, poor query performance has been reported. This could be caused by the following factors:
The order of the keys in the JSON was changed. Snowflake stores semi-structured data internally in a column-like structure for the most common elements, and the remainder in a leftovers-like column. The order of the keys in the JSON affects how Snowflake determines the common elements and how it optimizes the query performance. If the order of the keys in the JSON was changed, Snowflake might have to re-parse the data and re-organize the internal storage, which could result in slower query performance.
There were variations in string lengths for the JSON values in the recent data imports. Non-native values, such as dates and timestamps, are stored as strings when loaded into a VARIANT column.
Operations on these values could be slower and also consume more space than when stored in a relational column with the corresponding data type. If there were variations in string lengths for the JSON values in the recent data imports, Snowflake might have to allocate more space and perform more conversions, which could also result in slower query performance.
The other options are not valid causes for poor query performance:
There were JSON nulls in the recent data imports. Snowflake supports two types of null values in semi-structured data: SQL NULL and JSON null. SQL NULL means the value is missing or unknown, while JSON null means the value is explicitly set to null. Snowflake can distinguish between these two types of null values and handle them accordingly. Having JSON nulls in the recent data imports should not affect the query performance significantly.
The recent data imports contained fewer fields than usual. Snowflake can handle semi-structured data with varying schemas and fields. Having fewer fields than usual in the recent data imports should not affect the query performance significantly, as Snowflake can still optimize the data ingestion and query execution based on the existing fields.
References:
Considerations for Semi-structured Data Stored in VARIANT
Snowflake Architect Training
Snowflake query performance on unique element in variant column
Snowflake variant performance

QUESTION 62
The following DDL command was used to create a task based on a stream:

Assuming MY_WH is set to auto_suspend – 60 and used exclusively for this task, which statement is true?

The warehouse MY_WH will be made active every five minutes to check the stream.

The warehouse MY_WH will only be active when there are results in the stream.

The warehouse MY_WH will never suspend.

The warehouse MY_WH will automatically resize to accommodate the size of the stream.

QUESTION 63
Which feature provides the capability to define an alternate cluster key for a table with an existing cluster key?

External table

Materialized view

Search optimization

Result cache

QUESTION 64
You are a snowflake architect in an organization. The business team came to to deploy an use case which requires you to load some data which they can visualize through tableau. Everyday new data comes in and the old data is no longer required.
What type of table you will use in this case to optimize cost

TRANSIENT

TEMPORARY

PERMANENT

QUESTION 65
The IT Security team has identified that there is an ongoing credential stuffing attack on many of their organization’s system.
What is the BEST way to find recent and ongoing login attempts to Snowflake?

Call the LOGIN_HISTORY Information Schema table function.

Query the LOGIN_HISTORY view in the ACCOUNT_USAGE schema in the SNOWFLAKE database.

View the History tab in the Snowflake UI and set up a filter for SQL text that contains the text
“LOGIN”.

View the Users section in the Account tab in the Snowflake UI and review the last login column.

QUESTION 66
What Snowflake features should be leveraged when modeling using Data Vault?

Snowflake’s support of multi-table inserts into the data model’s Data Vault tables

Data needs to be pre-partitioned to obtain a superior data access performance

Scaling up the virtual warehouses will support parallel processing of new source loads

Snowflake’s ability to hash keys so that hash key joins can run faster than integer joins

QUESTION 67
A company’s Architect needs to find an efficient way to get data from an external partner, who is also a Snowflake user. The current solution is based on daily JSON extracts that are placed on an FTP server and uploaded to Snowflake manually. The files are changed several times each month, and the ingestion process needs to be adapted to accommodate these changes.
What would be the MOST efficient solution?

Ask the partner to create a share and add the company’s account.

Ask the partner to use the data lake export feature and place the data into cloud storage where Snowflake can natively ingest it (schema-on-read).

Keep the current structure but request that the partner stop changing files, instead only appending new files.

Ask the partner to set up a Snowflake reader account and use that account to get the data for ingestion.

The most efficient solution is to ask the partner to create a share and add the company’s account (Option A).
This way, the company can access the live data from the partner without any data movement or manual intervention. Snowflake’s secure datasharing feature allows data providers to share selected objects in a database with other Snowflake accounts. The shared data is read-only and does not incur any storage or compute costs for the data consumers. The data consumers can query the shared data directly or create local copies of the shared objects in their own databases. Option B is not efficient because it involves using the data lake export feature, which is intended for exporting data from Snowflake to an external data lake, not for importing data from another Snowflake account. The data lake export feature also requires the data provider to create an external stage on cloud storage and use the COPY INTO <location> command to export the data into parquet files. The data consumer then needs to create an external table or a file format to load the data from the cloud storage into Snowflake. This process can be complex and costly, especially if the data changes frequently. Option C is not efficient because it does not solve the problem of manual data ingestion and adaptation. Keeping the current structure of daily JSON extracts on an FTP server and requesting the partner to stop changing files, instead only appending new files, does not improve the efficiency or reliability of the data ingestion process. The company still needs to upload the data to Snowflake manually and deal with any schema changes or data quality issues. Option D is not efficient because it requires the partner to set up a Snowflake reader account and use that account to get the data for ingestion. A reader account is a special type of account that can only consume data from the provider account that created it. It is intended for data consumers who are not Snowflake customers and do not have a licensing agreement with Snowflake. A reader account is not suitable for data ingestion from another Snowflake account, as it does not allow uploading, modifying, or unloading data. The company would need to use external tools or interfaces to access the data from the reader account and load it into their own account, which can be slow and expensive. References: The answer can be verified from Snowflake’s official documentation on secure data sharing, data lake export, and reader accounts available on their website. Here are some relevant links:
Introduction to Secure Data Sharing | Snowflake Documentation
Data Lake Export Public Preview Is Now Available on Snowflake | Snowflake Blog Managing Reader Accounts | Snowflake Documentation

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[Q47-Q67] ARA-R01 Actual Questions – Instant Download Tests Free Updated Today!

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