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Snowflake ARA-C01 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Snowflake Architecture	30%	- Platform Architecture Design 1. Data sharing architecture 2. Cross-region and cross-cloud architecture 3. Multi-account strategies 4. Organization and account structure - Storage and Compute Design 1. Database and schema design 2. Warehouse sizing and scaling 3. Micro-partitions and clustering
Topic 2: Performance Optimization	20%	- Cost and Resource Optimization 1. Concurrency scaling 2. Resource monitors 3. Warehouse cost optimization - Query Performance 1. Materialized views 2. Search optimization service 3. Query profiling and tuning 4. Caching strategies
Topic 3: Accounts and Security	25%	- Access Control and Authentication 1. Role-based access control 2. Network policies 3. SSO and MFA 4. Data masking and row access policies - Governance and Compliance 1. Object ownership and privilege management 2. Encryption and security architecture 3. Data governance strategies
Topic 4: Data Engineering	25%	- Data Loading and Pipelines 1. Snowpipe and tasks 2. External stages and file formats 3. Bulk and continuous data loading 4. Streams and CDC - Data Transformation 1. ETL and ELT design 2. Data modeling strategies 3. Semi-structured data processing

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Snowflake SnowPro Advanced Architect Certification Sample Questions (Q51-Q56):

NEW QUESTION # 51
A company is designing a process for importing a large amount of loT JSON data from cloud storage into Snowflake. New sets of loT data get generated and uploaded approximately every 5 minutes.
Once the loT data is in Snowflake, the company needs up-to-date information from an external vendor to join to the data. This data is then presented to users through a dashboard that shows different levels of aggregation. The external vendor is a Snowflake customer.
What solution will MINIMIZE complexity and MAXIMIZE performance?

A. 1. Create a Snowpipe to bring the JSON data into Snowflake.
2. Use streams and tasks to trigger a transformation procedure when new JSON data arrives.
3. Ask the vendor to expose an API so an external function call can be made to join the vendor's data back to the loT data in a transformation procedure.
4. Create materialized views over the larger dataset to perform the aggregations required by the dashboard.
5. Give the materialized views access to the dashboard tool.
B. 1. Create an external table over the JSON data in cloud storage.
2. Create a task that runs every 5 minutes to run a transformation procedure on new data based on a saved timestamp.
3. Ask the vendor to create a data share with the required data that can be imported into the company's Snowflake account.
4. Join the vendor's data back to the loT data using a transformation procedure.
5. Create views over the larger dataset to perform the aggregations required by the dashboard.
6. Give the views access to the dashboard tool.
C. 1. Create an external table over the JSON data in cloud storage.
2. Create a task that runs every 5 minutes to run a transformation procedure on new data, based on a saved timestamp.
3. Ask the vendor to expose an API so an external function can be used to generate a call to join the data back to the loT data in the transformation procedure.
4. Give the transformed table access to the dashboard tool.
5. Perform the aggregations on the dashboard tool.
D. 1. Create a Snowpipe to bring the JSON data into Snowflake.
2. Use streams and tasks to trigger a transformation procedure when new JSON data arrives.
3. Ask the vendor to create a data share with the required data that is then imported into the Snowflake account.
4. Join the vendor's data back to the loT data in a transformation procedure
5. Create materialized views over the larger dataset to perform the aggregations required by the dashboard.
6. Give the materialized views access to the dashboard tool.

Answer: D

Explanation:
Using Snowpipe for continuous, automated data ingestion minimizes the need for manual intervention and ensures that data is available in Snowflake promptly after it is generated. Leveraging Snowflake's data sharing capabilities allows for efficient and secure access to the vendor's data without the need for complex API integrations. Materialized views provide pre-aggregated data for fast access, which is ideal for dashboards that require high performance1234.
Reference =
* Snowflake Documentation on Snowpipe4
* Snowflake Documentation on Secure Data Sharing2
* Best Practices for Data Ingestion with Snowflake1

NEW QUESTION # 52
A new table and streams are created with the following commands:
CREATE OR REPLACE TABLE LETTERS (ID INT, LETTER STRING) ;
CREATE OR REPLACE STREAM STREAM_1 ON TABLE LETTERS;
CREATE OR REPLACE STREAM STREAM_2 ON TABLE LETTERS APPEND_ONLY = TRUE;
The following operations are processed on the newly created table:
INSERT INTO LETTERS VALUES (1, 'A');
INSERT INTO LETTERS VALUES (2, 'B');
INSERT INTO LETTERS VALUES (3, 'C');
TRUNCATE TABLE LETTERS;
INSERT INTO LETTERS VALUES (4, 'D');
INSERT INTO LETTERS VALUES (5, 'E');
INSERT INTO LETTERS VALUES (6, 'F');
DELETE FROM LETTERS WHERE ID = 6;
What would be the output of the following SQL commands, in order?
SELECT COUNT (*) FROM STREAM_1;
SELECT COUNT (*) FROM STREAM_2;

A. 2 & 3
B. 4 & 3
C. 2 & 6
D. 4 & 6

Answer: B

Explanation:
In Snowflake, a stream records data manipulation language (DML) changes to its base table since the stream was created or last consumed. STREAM_1 will show all changes including the TRUNCATE operation, while STREAM_2, being APPEND_ONLY, will not show deletions like TRUNCATE. Therefore, STREAM_1 will count the three inserts, the TRUNCATE (counted as a single operation), and the subsequent two inserts before the delete, totaling 4. STREAM_2 will only count the three initial inserts and the two after the TRUNCATE, totaling 3, as it does not count the TRUNCATE or the delete operation.
References: The explanation is based on the Snowflake documentation on streams, which details how streams track changes and the difference between standard and APPEND_ONLY streams12.

NEW QUESTION # 53
What integration object should be used to place restrictions on where data may be exported?

A. API integration
B. Storage integration
C. Security integration
D. Stage integration

Answer: B

NEW QUESTION # 54
Shares are first-class objects in Snowflake for which Snowflake provides a set of DDL commands for creating and managing shares

A. TRUE
B. FALSE

Answer: A

NEW QUESTION # 55
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 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
C. 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
D. 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

Answer: B

Explanation:
Option C is the correct answer because it allows the company to share data privately with the customer across different cloud platforms and regions. The company can create a new Snowflake account in Azure East US 2 (Virginia) and set up replication between AWS us-west-2 (Oregon) and Azure East US 2 (Virginia) for the database objects to be shared. This way, the company can ensure that the data is always up to date and consistent in both accounts. The company can then create a share and add the database privileges to the share, and alter the share and add the customer's Snowflake account to the share. The customer can then access the shared data from their own Snowflake account in Azure East US 2 (Virginia).
Option A is incorrect because the Snowflake Marketplace is not a private way of sharing data. The Snowflake Marketplace is a public data exchange platform that allows anyone to browse and subscribe to data sets from various providers. The company would not be able to control who can access their data if they use the Snowflake Marketplace.
Option B is incorrect because it requires the customer to create a new Snowflake account in Azure East US 2 (Virginia), which may not be feasible or desirable for the customer. The customer may already have an existing Snowflake account in a different cloud platform or region, and may not want to incur additional costs or complexity by creating a new account.
Option D is incorrect because it involves creating a reader account in Azure East US 2 (Virginia), which is a limited and temporary way of sharing data. A reader account is a special type of Snowflake account that can only access data from a single share, and has a fixed duration of 30 days. The company would have to manage the reader account's URL and credentials, and renew the account every 30 days. The customer would not be able to use their own Snowflake account to access the shared data, and would have to rely on the company's reader account.
Reference:
Snowflake Replication
Secure Data Sharing Overview
Snowflake Marketplace Overview
Reader Account Overview

NEW QUESTION # 56
......

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