100% Real ARA-C01 dumps - Brilliant ARA-C01 Exam Questions PDF [Q69-Q90]

100% Real ARA-C01 dumps  - Brilliant ARA-C01 Exam Questions PDF

ARA-C01 Exam PDF [2025] Tests Free Updated Today with Correct 162 Questions

Snowflake ARA-C01: SnowPro Advanced Architect Certification is a highly recognized and sought-after certification for individuals who want to demonstrate their advanced knowledge and expertise in Snowflake's cloud data platform. SnowPro Advanced Architect Certification certification is designed for architects and advanced-level professionals who have experience in designing and implementing complex data solutions with Snowflake.

 

NEW QUESTION # 69
An Architect Is designing a data lake with Snowflake. The company has structured, semi-structured, and unstructured data. The company wants to save the data inside the data lake within the Snowflake system. The company is planning on sharing data among Its corporate branches using Snowflake data sharing.
What should be considered when sharing the unstructured data within Snowflake?

• A. A file URL should be used to save the unstructured data into Snowflake in order to share data over secure views, with a 7-day time limit for the URL.
• B. A file URL should be used to save the unstructured data into Snowflake in order to share data over secure views, with the "expiration_time" argument defined for the URL time limit.
• C. A pre-signed URL should be used to save the unstructured data into Snowflake in order to share data over secure views, with no time limit for the URL.
• D. A scoped URL should be used to save the unstructured data into Snowflake in order to share data over secure views, with a 24-hour time limit for the URL.

Answer: B

Explanation:
According to the Snowflake documentation, unstructured data files can be shared by using a secure view and Secure Data Sharing. A secure view allows the result of a query to be accessed like a table, and a secure view is specifically designated for data privacy. A scoped URL is an encoded URL that permits temporary access to a staged file without granting privileges to the stage. The URL expires when the persisted query result period ends, which is currently 24 hours. A scoped URL is recommended for file administrators to give scoped access to data files to specific roles in the same account. Snowflake records information in the query history about who uses a scoped URL to access a file, and when. Therefore, a scoped URL is the best option to share unstructured data within Snowflake, as it provides security, accountability, and control over the data access. References:
* Sharing unstructured Data with a secure view
* Introduction to Loading Unstructured Data

NEW QUESTION # 70
Materialized views based on external tables can improve query performance

• A. FALSE
• B. TRUE

Answer: B

NEW QUESTION # 71
An Architect has a design where files arrive every 10 minutes and are loaded into a primary database table using Snowpipe. A secondary database is refreshed every hour with the latest data from the primary database.
Based on this scenario, what Time Travel query options are available on the secondary database?

• A. Using Time Travel, secondary database users can query every iterative version within each hour (the individual Snowpipe loads) and outside the retention window.
• B. Using Time Travel, secondary database users can query every iterative version within each hour (the individual Snowpipe loads) in the retention window.
• C. A query using Time Travel in the secondary database is available for every hourly table version within the retention window.
• D. A query using Time Travel in the secondary database is available for every hourly table version within and outside the retention window.

Answer: C

Explanation:
Snowflake's Time Travel feature allows users to query historical data within a defined retention period. In the given scenario, since the secondary database is refreshed every hour, Time Travel can be used to query each hourly version of the table as long as it falls within the retention window. This does not include individual Snowpipe loads within each hour unless they coincide with the hourly refresh.

NEW QUESTION # 72
What transformations are supported in the below SQL statement? (Select THREE).
CREATE PIPE ... AS COPY ... FROM (...)

• A. Type casts are supported.
• B. The ON ERROR - ABORT statement command can be used.
• C. Columns can be omitted.
• D. Data can be filtered by an optional where clause.
• E. Incoming data can be joined with other tables.
• F. Columns can be reordered.

Answer: C,D,F

NEW QUESTION # 73
An Architect is troubleshooting a query with poor performance using the QUERY_HIST0RY function. The Architect observes that the COMPILATIONJHME is greater than the EXECUTIONJTIME.
What is the reason for this?

• A. The query is processing a very large dataset.
• B. The query is queued for execution.
• C. The query has overly complex logic.
• D. The query is reading from remote storage.

Answer: C

Explanation:
Compilation time is the time it takes for the optimizer to create an optimal query plan for the efficient execution of the query. It also involves some pruning of partition files, making the query execution efficient2 If the compilation time is greater than the execution time, it means that the optimizer spent more time analyzing the query than actually running it. This could indicate that the query has overly complex logic, such as multiple joins, subqueries, aggregations, or expressions. The complexity of the query could also affect the size and quality of the query plan, which could impact the performance of the query3 To reduce the compilation time, the Architect can try to simplify the query logic, use views or common table expressions (CTEs) to break down the query into smaller parts, or use hints to guide the optimizer. The Architect can also use the EXPLAIN command to examine the query plan and identify potential bottlenecks or inefficiencies4 References:
* 1: SnowPro Advanced: Architect | Study Guide 5
* 2: Snowflake Documentation | Query Profile Overview 6
* 3: Understanding Why Compilation Time in Snowflake Can Be Higher than Execution Time 7
* 4: Snowflake Documentation | Optimizing Query Performance 8
* : SnowPro Advanced: Architect | Study Guide
* : Query Profile Overview
* : Understanding Why Compilation Time in Snowflake Can Be Higher than Execution Time
* : Optimizing Query Performance

NEW QUESTION # 74
If you run the below commands in your worksheet, what will happen?
CREATE TEMP TABLE STUDENT_TABLE(STUID NUMBER, COURSE VARCHAR); CREATE TABLE
STUDENT_TABLE_CLONE
CLONE STUDENT_TABLE;

• A. SQL compilation error: Temp table cannot be cloned to a permanent table; clone to a transient table instead.
• B. A temporary table will be created with name as STUDENT_TABLE. The clone will create a clone of the STUDENT_TABLE
• C. You will get an error as below
• D. Only the STUDENT_TABLE_CLONE will be created, the other one will be deleted

Answer: A

NEW QUESTION # 75
Which command will create a schema without Fail-safe and will restrict object owners from passing on access to other users?

• A. create TRANSIENT schema EDW.ACCOUNTING WITH MANAGED ACCESS DATA_RETENTION_TIME_IN_DAYS = 7;
• B. create TRANSIENT schema EDW.ACCOUNTING WITH MANAGED ACCESS DATA_RETENTION_TIME_IN_DAYS = 1;
• C. create schema EDW.ACCOUNTING WITH MANAGED ACCESS;
• D. create schema EDW.ACCOUNTING WITH MANAGED ACCESS DATA_RETENTION_TIME_IN_DAYS - 7;

Answer: A

Explanation:
A transient schema in Snowflake is designed without a Fail-safe period, meaning it does not incur additional storage costs once it leaves Time Travel, and it is not protected by Fail-safe in the event of a data loss. The WITH MANAGED ACCESS option ensures that all privilege grants, including future grants on objects within the schema, are managed by the schema owner, thus restricting object owners from passing on access to other users1.
Reference =
* Snowflake Documentation on creating schemas1
* Snowflake Documentation on configuring access control2
* Snowflake Documentation on understanding and viewing Fail-safe3

NEW QUESTION # 76
A new user user_01 is created within Snowflake. The following two commands are executed:
Command 1-> show grants to user user_01;
Command 2 ~> show grants on user user 01;
What inferences can be made about these commands?

• A. Command 1 defines all the grants which are given to user_01
  Command 2 defines which role owns user 01
• B. Command 1 defines which role owns user_01
  Command 2 defines all the grants which have been given to user_01
• C. Command 1 defines all the grants which are given to user_01 Command 2 defines which user owns user_01
• D. Command 1 defines which user owns user_01
  Command 2 defines all the grants which have been given to user_01

Answer: D

NEW QUESTION # 77
What step will improve the performance of queries executed against an external table?

• A. Use an internal stage instead of an external stage to store the source files.
• B. Convert the source files' character encoding to UTF-8.
• C. Partition the external table.
• D. Shorten the names of the source files.

Answer: C

Explanation:
Partitioning an external table is a technique that improves the performance of queries executed against the table by reducing the amount of data scanned. Partitioning an external table involves creating one or more partition columns that define how the table is logically divided into subsets of data based on the values in those columns. The partition columns can be derived from the file metadata (such as file name, path, size, or modification time) or from the file content (such as a column value or a JSON attribute). Partitioning an external table allows the query optimizer to prune the files that do not match the query predicates, thus avoiding unnecessary data scanning and processing2 The other options are not effective steps for improving the performance of queries executed against an external table:
Shorten the names of the source files. This option does not have any impact on the query performance, as the file names are not used for query processing. The file names are only used for creating the external table and displaying the query results3 Convert the source files' character encoding to UTF-8. This option does not affect the query performance, as Snowflake supports various character encodings for external table files, such as UTF-8, UTF-16, UTF-32, ISO-8859-1, and Windows-1252. Snowflake automatically detects the character encoding of the files and converts them to UTF-8 internally for query processing4 Use an internal stage instead of an external stage to store the source files. This option is not applicable, as external tables can only reference files stored in external stages, such as Amazon S3, Google Cloud Storage, or Azure Blob Storage. Internal stages are used for loading data into internal tables, not external tables5 Reference:
1: SnowPro Advanced: Architect | Study Guide
2: Snowflake Documentation | Partitioning External Tables
3: Snowflake Documentation | Creating External Tables
4: Snowflake Documentation | Supported File Formats and Compression for Staged Data Files
5: Snowflake Documentation | Overview of Stages
: SnowPro Advanced: Architect | Study Guide
: Partitioning External Tables
: Creating External Tables
: Supported File Formats and Compression for Staged Data Files
: Overview of Stages

NEW QUESTION # 78
Which of the below commands will use warehouse credits?

• A. SHOW TABLES LIKE 'SNOWFL%';
• B. SELECT COUNT(*) FROM SNOWFLAKE;
• C. SELECT COUNT(FLAKE_ID) FROM SNOWFLAKE GROUP BY FLAKE_ID;
• D. SELECT MAX(FLAKE_ID) FROM SNOWFLAKE;

Answer: C

NEW QUESTION # 79
Which of the below privileges are required for search optimization?

• A. ADD SEARCH OPTIMIZATION privilege on the schema that contains the table
• B. ADD SEARCH OPTIMIZATION privilege on the table.
• C. OWNERSHIP privilege on the table

Answer: A,C

NEW QUESTION # 80
Consider the following COPY command which is loading data with CSV format into a Snowflake table from an internal stage through a data transformation query.

This command results in the following error:
SQL compilation error: invalid parameter 'validation_mode'
Assuming the syntax is correct, what is the cause of this error?

• A. The VALIDATION_MODE parameter supports COPY statements that load data from external stages only.
• B. The value return_all_errors of the option VALIDATION_MODE is causing a compilation error.
• C. The VALIDATION_MODE parameter does not support COPY statements that transform data during a load.
• D. The VALIDATION_MODE parameter does not support COPY statements with CSV file formats.

Answer: C

Explanation:
* The VALIDATION_MODE parameter is used to specify the behavior of the COPY statement when loading data into a table. It is used to specify whether the COPY statement should return an error if any of the rows in the file are invalid or if it should continue loading the valid rows. The VALIDATION_MODE parameter is only supported for COPY statements that load data from external stages1.
* The query in the question uses a data transformation query to load data from an internal stage. A data transformation query is a query that transforms the data during the load process, such as parsing JSON or XML data, applying functions, or joining with other tables2.
* According to the documentation, VALIDATION_MODE does not support COPY statements that transform data during a load. If the parameter is specified, the COPY statement returns an error1.
Therefore, option C is the correct answer.
References: : COPY INTO <table> : Transforming Data During a Load

NEW QUESTION # 81
An Architect would like to save quarter-end financial results for the previous six years.
Which Snowflake feature can the Architect use to accomplish this?

• A. Materialized view
• B. Zero-copy cloning
• C. Time Travel
• D. Secure views
• E. Search optimization service

Answer: B

NEW QUESTION # 82
Multi-cluster warehouses are best utilized for

• A. Scaling resources to improve concurrency for users/queries
• B. Improving the performance of data loading
• C. Improving the performance of slow-running queries

Answer: A

NEW QUESTION # 83
What actions are permitted when using the Snowflake SQL REST API? (Select TWO).

• A. Submitting multiple SQL statements in a single call
• B. The use of a ROLLBACK command
• C. The use of a GET command
• D. The use of a CALL command to a stored procedure which returns a table
• E. The use of a PUT command

Answer: C,D

Explanation:
A: The Snowflake SQL REST API does support the use of a GET command, which can be used to retrieve the status of a previously submitted query or to fetch the results of a query once it has been executed.
D: The use of a CALL command to a stored procedure is supported, which can return a result set, including a table. This allows the invocation of stored procedures within Snowflake through the SQL REST API.

NEW QUESTION # 84
Snowflake recommends starting slowly with SEARCH OPTIMIZATION(i.e. adding search optimization to only a few tables at first) and closely monitoring the costs and benefits.

• A. FALSE
• B. TRUE

Answer: B

NEW QUESTION # 85
Which of the following are characteristics of Snowflake's parameter hierarchy?

• A. Schema parameters override account parameters.
• B. Session parameters override virtual warehouse parameters.
• C. Virtual warehouse parameters override user parameters.
• D. Table parameters override virtual warehouse parameters.

Answer: A

Explanation:
Explanation
This is the correct answer because it reflects the characteristics of Snowflake's parameter hierarchy.
Snowflake provides three types of parameters that can be set for an account: account parameters, session parameters, and object parameters. All parameters have default values, which can be set and then overridden at different levels depending on the parameter type. The following diagram illustrates the hierarchical relationship between the different parameter types and how individual parameters can be overridden at each level1:
As shown in the diagram, schema parameters are a type of object parameters that can be set for schemas.
Schema parameters can override the account parameters that are set at the account level. For example, the LOG_LEVEL parameter can be set at the account level to control the logging level for all objects in the account, but it can also be overridden at the schema level to control the logging level for specific stored procedures and UDFs in that schema2.
The other options listed are not correct because they do not reflect the characteristics of Snowflake's parameter hierarchy. Session parameters do not override virtual warehouse parameters, because virtual warehouse parameters are a type of session parameters that can be set for virtual warehouses. Virtual warehouse parameters do not override user parameters, because user parameters are a type of session parameters that can be set for users. Table parameters do not override virtual warehouse parameters, because table parameters are a type of object parameters that can be set for tables, and object parameters do not affect session parameters1.
References:
* Snowflake Documentation: Parameters
* Snowflake Documentation: Setting Log Level

NEW QUESTION # 86
The Business Intelligence team reports that when some team members run queries for their dashboards in parallel with others, the query response time is getting significantly slower What can a Snowflake Architect do to identify what is occurring and troubleshoot this issue?

• A. A close up of text Description automatically generated
  
• B. A screen shot of a computer Description automatically generated
  
• C. A black text on a white background Description automatically generated
  
• D. A computer error message Description automatically generated
  

Answer: D

Explanation:
The image shows a SQL query that can be used to identify which queries are spilled to remote storage and suggests changing the warehouse parameters to address this issue. Spilling to remote storage occurs when the memory allocated to a warehouse is insufficient to process a query, and Snowflake uses disk or cloud storage as a temporary cache. This can significantly slow down the query performance and increase the cost. To troubleshoot this issue, a Snowflake Architect can run the query shown in the image to find out which queries are spilling, how much data they are spilling, and which warehouses they are using. Then, the architect can adjust the warehouse size, type, or scaling policy to provide enough memory for the queries and avoid spilling12. References:
* Recognizing Disk Spilling
* Managing the Kafka Connector

NEW QUESTION # 87
A company is storing large numbers of small JSON files (ranging from 1-4 bytes) that are received from IoT devices and sent to a cloud provider. In any given hour, 100,000 files are added to the cloud provider.
What is the MOST cost-effective way to bring this data into a Snowflake table?

• A. An external table
• B. A pipe
• C. A stream
• D. A copy command at regular intervals

Answer: B

Explanation:
Explanation
* A pipe is a Snowflake object that continuously loads data from files in a stage (internal or external) into a table. A pipe can be configured to use auto-ingest, which means that Snowflake automatically detects new or modified files in the stage and loads them into the table without any manual intervention1.
* A pipe is the most cost-effective way to bring large numbers of small JSON files into a Snowflake table, because it minimizes the number of COPY commands executed and the number of micro-partitions created. A pipe can use file aggregation, which means that it can combine multiple small files into a single larger file before loading them into the table. This reduces the load time and the storage cost of the data2.
* An external table is a Snowflake object that references data files stored in an external location, such as Amazon S3, Google Cloud Storage, or Microsoft Azure Blob Storage. An external table does not store the data in Snowflake, but only provides a view of the data for querying. An external table is not a cost-effective way to bring data into a Snowflake table, because it does not support file aggregation, and it requires additional network bandwidth and compute resources to query the external data3.
* A stream is a Snowflake object that records the history of changes (inserts, updates, and deletes) made to a table. A stream can be used to consume the changes from a table and apply them to another table or a task. A stream is not a way to bring data into a Snowflake table, but a way to process the data after it is loaded into a table4.
* A copy command is a Snowflake command that loads data from files in a stage into a table. A copy command can be executed manually or scheduled using a task. A copy command is not a cost-effective way to bring large numbers of small JSON files into a Snowflake table, because it does not support file aggregation, and it may create many micro-partitions that increase the storage cost of the data5.
References: : Pipes : Loading Data Using Snowpipe : External Tables : Streams : COPY INTO <table>

NEW QUESTION # 88
How can the Snowflake context functions be used to help determine whether a user is authorized to see data that has column-level security enforced? (Select TWO).

• A. Assign the accountadmin role to the user who is executing the object.
• B. Determine if there are ownership privileges on the masking policy that would allow the use of any function.
• C. Set masking policy conditions using is_role_in_session targeting the role in use for the current account.
• D. Set masking policy conditions using invoker_role targeting the executing role in a SQL statement.
• E. Set masking policy conditions using current_role targeting the role in use for the current session.

Answer: D,E

Explanation:
Snowflake context functions are functions that return information about the current session, user, role, warehouse, database, schema, or object. They can be used to help determine whether a user is authorized to see data that has column-level security enforced by setting masking policy conditions based on the context functions. The following context functions are relevant for column-level security:
current_role: This function returns the name of the role in use for the current session. It can be used to set masking policy conditions that target the current session and are not affected by the execution context of the SQL statement. For example, a masking policy condition using current_role can allow or deny access to a column based on the role that the user activated in the session.
invoker_role: This function returns the name of the executing role in a SQL statement. It can be used to set masking policy conditions that target the executing role and are affected by the execution context of the SQL statement. For example, a masking policy condition using invoker_role can allow or deny access to a column based on the role that the user specified in the SQL statement, such as using the AS ROLE clause or a stored procedure.
is_role_in_session: This function returns TRUE if the user's current role in the session (i.e. the role returned by current_role) inherits the privileges of the specified role. It can be used to set masking policy conditions that involve role hierarchy and privilege inheritance. For example, a masking policy condition using is_role_in_session can allow or deny access to a column based on whether the user's current role is a lower privilege role in the specified role hierarchy.
The other options are not valid ways to use the Snowflake context functions for column-level security:
Set masking policy conditions using is_role_in_session targeting the role in use for the current account. This option is incorrect because is_role_in_session does not target the role in use for the current account, but rather the role in use for the current session. Also, the current account is not a role, but rather a logical entity that contains users, roles, warehouses, databases, and other objects.
Determine if there are ownership privileges on the masking policy that would allow the use of any function. This option is incorrect because ownership privileges on the masking policy do not affect the use of any function, but rather the ability to create, alter, or drop the masking policy. Also, this is not a way to use the Snowflake context functions, but rather a way to check the privileges on the masking policy object.
Assign the accountadmin role to the user who is executing the object. This option is incorrect because assigning the accountadmin role to the user who is executing the object does not involve using the Snowflake context functions, but rather granting the highest-level role to the user. Also, this is not a recommended practice for column-level security, as it would give the user full access to all objects and data in the account, which could compromise data security and governance.
Reference:
Context Functions
Advanced Column-level Security topics
Snowflake Data Governance: Column Level Security Overview
Data Security Snowflake Part 2 - Column Level Security

NEW QUESTION # 89
A Snowflake Architect Is working with Data Modelers and Table Designers to draft an ELT framework specifically for data loading using Snowpipe. The Table Designers will add a timestamp column that Inserts the current tlmestamp as the default value as records are loaded into a table. The Intent is to capture the time when each record gets loaded into the table; however, when tested the timestamps are earlier than the loae_take column values returned by the copy_history function or the Copy_HISTORY view (Account Usage).
Why Is this occurring?

• A. The Snowflake timezone parameter Is different from the cloud provider's parameters causing the mismatch.
• B. The CURRENT_TIMEis evaluated when the load operation is compiled in cloud services rather than when the record is inserted into the table.
• C. The timestamps are different because there are parameter setup mismatches. The parameters need to be realigned
• D. The Table Designer team has not used the localtimestamp or systimestamp functions in the Snowflake copy statement.

Answer: B

Explanation:
* The correct answer is D because the CURRENT_TIME function returns the current timestamp at the start of the statement execution, not at the time of the record insertion. Therefore, if the load operation takes some time to complete, the CURRENT_TIME value may be earlier than the actual load time.
* Option A is incorrect because the parameter setup mismatches do not affect the timestamp values. The parameters are used to control the behavior and performance of the load operation, such as the file format, the error handling, the purge option, etc.
* Option B is incorrect because the Snowflake timezone parameter and the cloud provider's parameters are independent of each other. The Snowflake timezone parameter determines the session timezone for displaying and converting timestamp values, while the cloud provider's parameters determine the
* physical location and configuration of the storage and compute resources.
* Option C is incorrect because the localtimestamp and systimestamp functions are not relevant for the Snowpipe load operation. The localtimestamp function returns the current timestamp in the session timezone, while the systimestamp function returns the current timestamp in the system timezone.
Neither of them reflect the actual load time of the records. References:
* Snowflake Documentation: Loading Data Using Snowpipe: This document explains how to use Snowpipe to continuously load data from external sources into Snowflake tables. It also describes the syntax and usage of the COPY INTO command, which supports various options and parameters to control the loading behavior.
* Snowflake Documentation: Date and Time Data Types and Functions: This document explains the different data types and functions for working with date and time values in Snowflake. It also describes how to set and change the session timezone and the system timezone.
* Snowflake Documentation: Querying Metadata: This document explains how to query the metadata of the objects and operations in Snowflake using various functions, views, and tables. It also describes how to access the copy history information using the COPY_HISTORY function or the COPY_HISTORY view.

NEW QUESTION # 90
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