Reliable SnowPro Advanced Certification ARA-C01 Dumps PDF Feb 11, 2024 Recently Updated Questions

Pass Your Snowflake ARA-C01 Exam with Correct 65 Questions and Answers

NEW QUESTION # 37
External functions must be scalar functions

• A. FALSE
• B. TRUE

Answer: B

NEW QUESTION # 38
An Architect uses COPY INTO with the ON_ERROR=SKIP_FILE option to bulk load CSV files into a table called TABLEA, using its table stage. One file named file5.csv fails to load. The Architect fixes the file and re-loads it to the stage with the exact same file name it had previously.
Which commands should the Architect use to load only file5.csv file from the stage? (Choose two.)

• A. COPY INTO tablea FROM @%tablea RETURN_FAILED_ONLY = TRUE;
• B. COPY INTO tablea FROM @%tablea FORCE = TRUE;
• C. COPY INTO tablea FROM @%tablea;
• D. COPY INTO tablea FROM @%tablea NEW_FILES_ONLY = TRUE;
• E. COPY INTO tablea FROM @%tablea MERGE = TRUE;
• F. COPY INTO tablea FROM @%tablea FILES = ('file5.csv');

Answer: C,D

NEW QUESTION # 39
A company has an inbound share set up with eight tables and five secure views. The company plans to make the share part of its production data pipelines.
Which actions can the company take with the inbound share? (Choose two.)

• A. Clone a table from a share.
• B. Create a table from the shared database.
• C. Create a table stream on the shared table.
• D. Create additional views inside the shared database.
• E. Grant modify permissions on the share.

Answer: B,C

NEW QUESTION # 40
Which command do you run to remove files from stage?

• A. DELETE
• B. REMOVE
• C. PURGE
• D. CLEAN

Answer: B

NEW QUESTION # 41
Select the true statement

• A. Privileges are granted to users. Users are granted to roles
• B. Privileges are granted to both roles and users
• C. Privileges are granted to roles. Roles are granted to users

Answer: C

NEW QUESTION # 42
Which semi-structured data function returns an OBJECT constructed from the arguments.

• A. OBJECT_INSPECT
• B. OBJECT_ARRAY
• C. OBJECT_CONSTRUCT

Answer: C

NEW QUESTION # 43
What is a characteristic of loading data into Snowflake using the Snowflake Connector for Kafka?

• A. Loads using the Connector will have lower latency than Snowpipe and will ingest data in real time.
• B. The Connector works with all file formats, including text, JSON, Avro, Ore, Parquet, and XML.
• C. The Connector only works in Snowflake regions that use AWS infrastructure.
• D. The Connector creates and manages its own stage, file format, and pipe objects.

Answer: D

Explanation:
Explanation
According to the SnowPro Advanced: Architect documents and learning resources, a characteristic of loading data into Snowflake using the Snowflake Connector for Kafka is that the Connector creates and manages its own stage, file format, and pipe objects. The stage is an internal stage that is used to store the data files from the Kafka topics. The file format is a JSON or Avro file format that is used to parse the data files. The pipe is a Snowpipe object that is used to load the data files into the Snowflake table. The Connector automatically creates and configures these objects based on the Kafka configuration properties, and handles the cleanup and maintenance of these objects1.
The other options are incorrect because they are not characteristics of loading data into Snowflake using the Snowflake Connector for Kafka. Option A is incorrect because the Connector works in Snowflake regions that use any cloud infrastructure, not just AWS. The Connector supports AWS, Azure, and Google Cloud platforms, and can load data across different regions and cloud platforms using data replication2. Option B is incorrect because the Connector does not work with all file formats, only JSON and Avro. The Connector expects the data in the Kafka topics to be in JSON or Avro format, and parses the data accordingly. Other file formats, such as text, ORC, Parquet, or XML, are not supported by the Connector3. Option D is incorrect because loads using the Connector do not have lower latency than Snowpipe, and do not ingest data in real time. The Connector uses Snowpipe to load data into Snowflake, and inherits the same latency and performance characteristics of Snowpipe. The Connector does not provide real-time ingestion, but near real-time ingestion, depending on the frequency and size of the data files4. References: Installing and Configuring the Kafka Connector | Snowflake Documentation, Sharing Data Across Regions and Cloud Platforms | Snowflake Documentation, Overview of the Kafka Connector | Snowflake Documentation, Using Snowflake Connector for Kafka With Snowpipe Streaming | Snowflake Documentation

NEW QUESTION # 44
One of your colleagues has submitted a long running query in Snowflake. how long the query can run till snowflake automatically cancels the query?

• A. 2 hours
• B. 2 days
• C. 14 hours
• D. 24 hours

Answer: B

NEW QUESTION # 45
Which role in Snowflake allows a user to administer users and manage all database objects?

• A. SECURITYADMIN
• B. SYSADMIN
• C. ACCOUNTADMIN
• D. ROOT

Answer: C

NEW QUESTION # 46
A healthcare company wants to share data with a medical institute. The institute is running a Standard edition of Snowflake; the healthcare company is running a Business Critical edition.
How can this data be shared?

• A. By default, sharing is supported from a Business Critical Snowflake edition to a Standard edition.
• B. Set the share_restriction parameter on the shared object to false.
• C. Contact Snowflake and they will execute the share request for the healthcare company.
• D. The healthcare company will need to change the institute's Snowflake edition in the accounts panel.

Answer: B

Explanation:
Explanation
By default, Snowflake does not allow sharing data from a Business Critical edition to a non-Business Critical edition. This is because Business Critical edition provides enhanced security and data protection features that are not available in lower editions. However, this restriction can be overridden by setting the share_restriction parameter on the shared object (database, schema, or table) to false. This parameter allows the data provider to explicitly allow sharing data with lower edition accounts. Note that this parameter can only be set by the data provider, not the data consumer. Also, setting this parameter to false may reduce the level of security and data protection for the shared data.
References:
* Enable Data Share:Business Critical Account to Lower Edition
* Sharing Is Not Allowed From An Account on BUSINESS CRITICAL Edition to an Account On A Lower Edition
* SQL Execution Error: Sharing is Not Allowed from an Account on BUSINESS CRITICAL Edition to an Account on a Lower Edition
* Snowflake Editions | Snowflake Documentation

NEW QUESTION # 47
A company's client application supports multiple authentication methods, and is using Okta.
What is the best practice recommendation for the order of priority when applications authenticate to Snowflake?

• A. 1) External browser, SSO
  2) Key Pair Authentication, mostly used for development environment users
  3) Okta native authentication
  4) OAuth (ether Snowflake OAuth or External OAuth)
  5) Password
• B. 1) Password
  2) Key Pair Authentication, mostly used for production environment users
  3) Okta native authentication
  4) OAuth (either Snowflake OAuth or External OAuth)
  5) External browser, SSO
• C. 1) Okta native authentication
  2) Key Pair Authentication, mostly used for production environment users
  3) Password
  4) OAuth (either Snowflake OAuth or External OAuth)
  5) External browser, SSO
• D. 1) OAuth (either Snowflake OAuth or External OAuth)
  2) External browser
  3) Okta native authentication
  4) Key Pair Authentication, mostly used for service account users
  5) Password

Answer: A

NEW QUESTION # 48
An Architect runs the following SQL query:

How can this query be interpreted?

• A. FILERONS is the file format location. FILE_ROW_NUMBER is a stage.
• B. FILEROWS is a file. FILE_ROW_NUMBER is the file format location.
• C. FILEROWS is a stage. FILE_ROW_NUMBER is line number in file.
• D. FILEROWS is the table. FILE_ROW_NUMBER is the line number in the table.

Answer: C

NEW QUESTION # 49
The Data Engineering team at a large manufacturing company needs to engineer data coming from many sources to support a wide variety of use cases and data consumer requirements which include:
1) Finance and Vendor Management team members who require reporting and visualization
2) Data Science team members who require access to raw data for ML model development
3) Sales team members who require engineered and protected data for data monetization What Snowflake data modeling approaches will meet these requirements? (Choose two.)

• A. Create a raw database for landing and persisting raw data entering the data pipelines.
• B. Create a set of profile-specific databases that aligns data with usage patterns.
• C. Create a Data Vault as the sole data pipeline endpoint and have all consumers directly access the Vault.
• D. Consolidate data in the company's data lake and use EXTERNAL TABLES.
• E. Create a single star schema in a single database to support all consumers' requirements.

Answer: A,B

Explanation:
Explanation
These two approaches are recommended by Snowflake for data modeling in a data lake scenario. Creating a raw database allows the data engineering team to ingest data from various sources without any transformation or cleansing, preserving the original data quality and format. This enables the data science team to access the raw data for ML model development. Creating a set of profile-specific databases allows the data engineering team to apply different transformations and optimizations for different use cases and data consumer requirements. For example, the finance and vendor management team can access a dimensional database that supports reporting and visualization, while the sales team can access a secure database that supports data monetization.
References:
* Snowflake Data Lake Architecture | Snowflake Documentation
* Snowflake Data Lake Best Practices | Snowflake Documentation

NEW QUESTION # 50
A media company needs a data pipeline that will ingest customer review data into a Snowflake table, and apply some transformations. The company also needs to use Amazon Comprehend to do sentiment analysis and make the de-identified final data set available publicly for advertising companies who use different cloud providers in different regions.
The data pipeline needs to run continuously ang efficiently as new records arrive in the object storage leveraging event notifications. Also, the operational complexity, maintenance of the infrastructure, including platform upgrades and security, and the development effort should be minimal.
Which design will meet these requirements?

• A. Ingest the data using Snowpipe and use streams and tasks to orchestrate transformations. Export the data into Amazon S3 to do model inference with Amazon Comprehend and ingest the data back into a Snowflake table. Then create a listing in the Snowflake Marketplace to make the data available to other companies.
• B. Ingest the data into Snowflake using Amazon EMR and PySpark using the Snowflake Spark connector.
  Apply transformations using another Spark job. Develop a python program to do model inference by leveraging the Amazon Comprehend text analysis API. Then write the results to a Snowflake table and create a listing in the Snowflake Marketplace to make the data available to other companies.
• C. Ingest the data using Snowpipe and use streams and tasks to orchestrate transformations. Create an external function to do model inference with Amazon Comprehend and write the final records to a Snowflake table. Then create a listing in the Snowflake Marketplace to make the data available to other companies.
• D. Ingest the data using COPY INTO and use streams and tasks to orchestrate transformations. Export the data into Amazon S3 to do model inference with Amazon Comprehend and ingest the data back into a Snowflake table. Then create a listing in the Snowflake Marketplace to make the data available to other companies.

Answer: C

Explanation:
Explanation
This design meets all the requirements for the data pipeline. Snowpipe is a feature that enables continuous data loading into Snowflake from object storage using event notifications. It is efficient, scalable, and serverless, meaning it does not require any infrastructure or maintenance from the user. Streams and tasks are features that enable automated data pipelines within Snowflake, using change data capture and scheduled execution.
They are also efficient, scalable, and serverless, and they simplify the data transformation process. External functions are functions that can invoke external services or APIs from within Snowflake. They can be used to integrate with Amazon Comprehend and perform sentiment analysis on the data. The results can be written back to a Snowflake table using standard SQL commands. Snowflake Marketplace is a platform that allows data providers to share data with data consumers across different accounts, regions, and cloud platforms. It is a secure and easy way to make data publicly available to other companies.
References:
* Snowpipe Overview | Snowflake Documentation
* Introduction to Data Pipelines | Snowflake Documentation
* External Functions Overview | Snowflake Documentation
* Snowflake Data Marketplace Overview | Snowflake Documentation

NEW QUESTION # 51
You want to automatically delete the files from stage after a successful load using the COPY INTO command.
What will be recommended approach for deletion?

• A. No need to do anything, snowflake does it automatically
• B. Set REMOVE=TRUE in the COPY INTO Command
• C. Set PURGE=TRUE in the COPY INTO command

Answer: C

NEW QUESTION # 52
COMPRESSION = AUTO can automatically detect below compression techniques when FORMAT TYPE is CSV

• A. RAW_DEFLATE
• B. ZSTD
• C. BROTLI
• D. DEFLATE
• E. GZIP
• F. BZ2

Answer: A,B,D,E,F

NEW QUESTION # 53
Data loading transformation as part of copying data to a table from stage supports selecting data from user stage and named stages(internal and external) only

• A. FALSE
• B. TRUE

Answer: B

NEW QUESTION # 54
A user needs access to create materialized view on a shema mydb.myschema.
What is the appropriate command to provide the access?

• A. GRANT CREATE MATERIALIZED VIEW ON SCHEMA MYDB.MYSCHEMA TO USER USER1;
• B. GRANT ROLE MYROLE TO USER USER1; GRANT CREATE MATERIALIZED VIEW ON SCHEMA MYDB.MYSCHEMA TO MYROLE;
• C. GRANT CREATE MATERIALIZED VIEW ON SCHEMA MYDB.MYSCHEMA TO USER1;

Answer: B

NEW QUESTION # 55
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