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Snowflake ARA-C01 Exam Syllabus Topics:

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

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Snowflake SnowPro Advanced Architect Certification Sample Questions (Q78-Q83):

NEW QUESTION # 78
One of your joins is taking a lot of time. The query profile view looks like this.
What may be the issue?

A. Looks like tablescan is the most expensive operation in the profile.
B. There is not enough memory to process the join query
C. This may be an "exploding join" issue. The query has provided a condition where records from one table match multiple records from another table resulting in a cartesian product

Answer: C

NEW QUESTION # 79
What is a characteristic of loading data into Snowflake using the Snowflake Connector for Kafka?

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

Answer: B

NEW QUESTION # 80
How is the change of local time due to daylight savings time handled in Snowflake tasks? (Choose two.)

A. A task will move to a suspended state during the daylight savings time change.
B. A task schedule will follow only the specified time and will fail to handle lost or duplicated hours.
C. A task scheduled in a UTC-based schedule will have no issues with the time changes.
D. A frequent task execution schedule like minutes may not cause a problem, but will affect the task history.
E. Task schedules can be designed to follow specified or local time zones to accommodate the time changes.

Answer: C,E

Explanation:
According to the Snowflake documentation1 and the web search results2, these two statements are true about how the change of local time due to daylight savings time is handled in Snowflake tasks. A task is a feature that allows scheduling and executing SQL statements or stored procedures in Snowflake. A task can be scheduled using a cron expression that specifies the frequency and time zone of the task execution.
* A task scheduled in a UTC-based schedule will have no issues with the time changes. UTC is a universal time standard that does not observe daylight savings time. Therefore, a task that uses UTC as the time zone will run at the same time throughout the year, regardless of the local time changes1.
* Task schedules can be designed to follow specified or local time zones to accommodate the time changes. Snowflake supports using any valid IANA time zone identifier in the cron expression for a task. This allows the task to run according to the local time of the specified time zone, which may include daylight savings time adjustments. For example, a task that uses Europe/London as the time zone will run one hour earlier or later when the local time switches between GMT and BST12.
Snowflake Documentation: Scheduling Tasks
Snowflake Community: Do the timezones used in scheduling tasks in Snowflake adhere to daylight savings?

NEW QUESTION # 81
What are characteristics of the use of transactions in Snowflake? (Select TWO).

A. Explicit transactions should contain only DML statements and query statements. All DDL statements implicitly commit active transactions.
B. A transaction can be started explicitly by executing a begin work statement and end explicitly by executing a commit work statement.
C. The autocommit setting can be changed inside a stored procedure.
D. Explicit transactions can contain DDL, DML, and query statements.
E. A transaction can be started explicitly by executing a begin transaction statement and end explicitly by executing an end transaction statement.

Answer: B,D

Explanation:
A: Snowflake's transactions can indeed include DDL (Data Definition Language), DML (Data Manipulation Language), and query statements. When executed within a transaction block, they all contribute to the atomicity of the transaction-either all of them commit together or none at all.C. Snowflake supports explicit transaction control through the use of the BEGIN TRANSACTION (or simply BEGIN) and COMMIT statements. Alternatively, the BEGIN WORK and COMMIT WORK syntax is also supported, which is a standard SQL syntax for initiating and ending transactions, respectively.Note: The END TRANSACTION statement is not used in Snowflake to end a transaction; the correct statement is COMMIT or COMMIT WORK.

NEW QUESTION # 82
A large manufacturing company runs a dozen individual Snowflake accounts across its business divisions. The company wants to increase the level of data sharing to support supply chain optimizations and increase its purchasing leverage with multiple vendors.
The company's Snowflake Architects need to design a solution that would allow the business divisions to decide what to share, while minimizing the level of effort spent on configuration and management. Most of the company divisions use Snowflake accounts in the same cloud deployments with a few exceptions for European-based divisions.
According to Snowflake recommended best practice, how should these requirements be met?

A. Deploy to the Snowflake Marketplace making sure that invoker_share() is used in all secure views.
B. Migrate the European accounts in the global region and manage shares in a connected graph architecture. Deploy a Data Exchange.
C. Deploy a Private Data Exchange in combination with data shares for the European accounts.
D. Deploy a Private Data Exchange and use replication to allow European data shares in the Exchange.

Answer: D

Explanation:
According to Snowflake recommended best practice, the requirements of the large manufacturing company should be met by deploying a Private Data Exchange in combination with data shares for the European accounts. A Private Data Exchange is a feature of the Snowflake Data Cloud platform that enables secure and governed sharing of data between organizations. It allows Snowflake customers to create their own data hub and invite other parts of their organization or external partners to access and contribute data sets. A Private Data Exchange provides centralized management, granular access control, and data usage metrics for the data shared in the exchange1. A data share is a secure and direct way of sharing data between Snowflake accounts without having to copy or move the data. A data share allows the data provider to grant privileges on selected objects in their account to one or more data consumers in other accounts2. By using a Private Data Exchange in combination with data shares, the company can achieve the following benefits:
* The business divisions can decide what data to share and publish it to the Private Data Exchange, where it can be discovered and accessed by other members of the exchange. This reduces the effort and complexity of managing multiple data sharing relationships and configurations.
* The company can leverage the existing Snowflake accounts in the same cloud deployments to create the Private Data Exchange and invite the members to join. This minimizes the migration and setup costs and leverages the existing Snowflake features and security.
* The company can use data shares to share data with the European accounts that are in different regions or cloud platforms. This allows the company to comply with the regional and regulatory requirements for data sovereignty and privacy, while still enabling data collaboration across the organization.
* The company can use the Snowflake Data Cloud platform to perform data analysis and transformation
* on the shared data, as well as integrate with other data sources and applications. This enables the company to optimize its supply chain and increase its purchasing leverage with multiple vendors.

NEW QUESTION # 83
......

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