TEST ARA-C01 SIMULATOR, ARA-C01 TRAINING MATERIAL

Test ARA-C01 Simulator, ARA-C01 Training Material

Test ARA-C01 Simulator, ARA-C01 Training Material

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Snowflake ARA-C01 exam consists of multiple-choice questions that cover a wide range of topics related to data warehousing and cloud computing. ARA-C01 exam is timed, with a total duration of 120 minutes, and candidates must achieve a minimum score of 80% to pass. ARA-C01 exam is available in multiple languages including English, Japanese, and Spanish.

Snowflake ARA-C01 (SnowPro Advanced Architect Certification) Certification Exam is designed to test the ability of experienced Snowflake architects to design and implement complex Snowflake solutions. SnowPro Advanced Architect Certification certification exam is intended for professionals who have extensive experience in architecting Snowflake solutions and want to demonstrate their expertise and proficiency. ARA-C01 Exam assesses the candidate's ability to design, plan, and implement Snowflake solutions in a variety of scenarios.

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Snowflake SnowPro Advanced Architect Certification Sample Questions (Q27-Q32):

NEW QUESTION # 27
A company has a Snowflake environment running in AWS us-west-2 (Oregon). The company needs to share data privately with a customer who is running their Snowflake environment in Azure East US 2 (Virginia).
What is the recommended sequence of operations that must be followed to meet this requirement?

  • A. 1. Ask the customer to create a new Snowflake account in Azure EAST US 2 (Virginia)
    2. Create a share and add the database privileges to the share
    3. Alter the share and add the customer's Snowflake account to the share
  • B. 1. Create a share and add the database privileges to the share
    2. Create a new listing on the Snowflake Marketplace
    3. Alter the listing and add the share
    4. Instruct the customer to subscribe to the listing on the Snowflake Marketplace
  • C. 1. Create a new Snowflake account in Azure East US 2 (Virginia)
    2. Set up replication between AWS us-west-2 (Oregon) and Azure East US 2 (Virginia) for the database objects to be shared
    3. Create a share and add the database privileges to the share
    4. Alter the share and add the customer's Snowflake account to the share
  • D. 1. Create a reader account in Azure East US 2 (Virginia)
    2. Create a share and add the database privileges to the share
    3. Add the reader account to the share
    4. Share the reader account's URL and credentials with the customer

Answer: B


NEW QUESTION # 28
What are some of the characteristics of result set caches? (Choose three.)

  • A. The retention period can be reset for a maximum of 31 days.
  • B. Snowflake persists the data results for 24 hours.
  • C. Each time persisted results for a query are used, a 24-hour retention period is reset.
  • D. Time Travel queries can be executed against the result set cache.
  • E. The result set cache is not shared between warehouses.
  • F. The data stored in the result cache will contribute to storage costs.

Answer: A,B,C

Explanation:
Comprehensive and Detailed Explanation: According to the SnowPro Advanced: Architect documents and learning resources, some of the characteristics of result set caches are:
* Snowflake persists the data results for 24 hours. This means that the result set cache holds the results of every query executed in the past 24 hours, and can be reused if the same query is submitted again and the underlying data has not changed1.
* Each time persisted results for a query are used, a 24-hour retention period is reset. This means that the result set cache extends the lifetime of the results every time they are reused, up to a maximum of 31 days from the date and time that the query was first executed1.
* The retention period can be reset for a maximum of 31 days. This means that the result set cache will purge the results after 31 days, regardless of whether they are reused or not. After 31 days, the next time the query is submitted, a new result is generated and persisted1.
The other options are incorrect because they are not characteristics of result set caches. Option A is incorrect because Time Travel queries cannot be executed against the result set cache. Time Travel queries use the AS OF clause to access historical data that is stored in the storage layer, not the result set cache2. Option D is incorrect because the data stored in the result set cache does not contribute to storage costs. The result set cache is maintained by the service layer, and does not incur any additional charges1. Option F is incorrect because the result set cache is shared between warehouses. The result set cache is available across virtual warehouses, so query results returned to one user are available to any other user on the system who executes the same query, provided the underlying data has not changed1. References: Using Persisted Query Results | Snowflake Documentation, Time Travel | Snowflake Documentation


NEW QUESTION # 29
A company wants to deploy its Snowflake accounts inside its corporate network with no visibility on the internet. The company is using a VPN infrastructure and Virtual Desktop Infrastructure (VDI) for its Snowflake users. The company also wants to re-use the login credentials set up for the VDI to eliminate redundancy when managing logins.
What Snowflake functionality should be used to meet these requirements? (Choose two.)

  • A. Use private connectivity from a cloud provider.
  • B. Use a proxy Snowflake account outside the VPN, enabling client redirect for user logins.
  • C. Provision a unique company Tri-Secret Secure key.
  • D. Set up SSO for federated authentication.
  • E. Set up replication to allow users to connect from outside the company VPN.

Answer: B,C


NEW QUESTION # 30
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?

  • A. There were JSON nulls in the recent data imports.
  • B. There were variations in string lengths for the JSON values in the recent data imports.
  • C. The order of the keys in the JSON was changed.
  • D. The recent data imports contained fewer fields than usual.

Answer: C

Explanation:
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.
Reference:
Considerations for Semi-structured Data Stored in VARIANT
Snowflake Architect Training
Snowflake query performance on unique element in variant column
Snowflake variant performance


NEW QUESTION # 31
How do Snowflake databases that are created from shares differ from standard databases that are not created from shares? (Choose three.)

  • A. Shared databases will have the PUBLIC or INFORMATION_SCHEMA schemas without explicitly granting these schemas to the share.
  • B. Shared databases can also be created as transient databases.
  • C. Shared databases must be refreshed in order for new data to be visible.
  • D. Shared databases are not supported by Time Travel.
  • E. Shared databases cannot be cloned.
  • F. Shared databases are read-only.

Answer: D,E,F

Explanation:
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


NEW QUESTION # 32
......

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