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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Snowflake Architecture | 30% | - Data protection and recovery strategies - Object hierarchy and architectural impact - Data modeling and use cases - Development lifecycle and workload support - Data sharing architecture design |
| Topic 2: Accounts and Security | 25% | - Security principles and implementation scenarios - Account and database strategy design - Security, compliance and governance architecture |
| Topic 3: Performance Optimization | 20% | - Clustering and partitioning strategies - Cost optimization and resource management - Query performance tuning - Virtual warehouse configuration and sizing |
| Topic 4: Data Engineering | 25% | - Transformation and processing frameworks - Data loading and unloading solutions - Data pipeline and integration design |
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NEW QUESTION # 190
An Architect wants to build an automated ETL pipeline that reads data from an external stage using an external table, performs transformations on changed data, joins with dimension tables, and loads results into a target table.
What should the Architect use?
Answer: B
Explanation:
Streams and tasks provide Snowflake's native framework for building automated, incremental ETL pipelines.
A stream can track changes in the external table (or staging table), while tasks orchestrate the execution of transformation logic and loading into target tables (Answer A).
This approach supports complex transformations, joins with dimension tables, and controlled scheduling or event-driven execution. Materialized views cannot perform joins with arbitrary tables and are not suitable for complex ETL. Dynamic tables simplify transformations but are not designed to consume change data directly from external tables. Snowpipe focuses on ingestion only and does not support downstream transformations.
SnowPro Architect exams frequently test understanding of when to use streams and tasks versus newer abstractions like dynamic tables.
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NEW QUESTION # 191
An Architect needs to automate the daily Import of two files from an external stage into Snowflake. One file has Parquet-formatted data, the other has CSV-formatted data.
How should the data be joined and aggregated to produce a final result set?
Answer: A
Explanation:
According to the Snowflake documentation, tasks are objects that enable scheduling and execution of SQL statements or JavaScript user-defined functions (UDFs) in Snowflake. Tasks can be used to automate data loading, transformation, and maintenance operations. Snowflake scripting is a feature that allows writing procedural logic using SQL statements and JavaScript UDFs. Snowflake scripting can be used to create complex workflows and orchestrate tasks. Therefore, the best option to automate the daily import of two files from an external stage into Snowflake, join and aggregate the data, and produce a final result set is to create a task using Snowflake scripting that will import the files using the COPY INTO command, and then call a UDF to perform the join and aggregation logic. The UDF can return a table or a variant value as the final result set. References:
* Tasks
* Snowflake Scripting
* User-Defined Functions
NEW QUESTION # 192
A user is executing the following command sequentially within a timeframe of 10 minutes from start to finish:
What would be the output of this query?
Answer: B
Explanation:
The query is executing a clone operation on an existing table t_sales with an offset to account for the retention time. The syntax used is correct for cloning a table in Snowflake, and the use of the at(offset => -60*30) clause is valid. This specifies that the clone should be based on the state of the table 30 minutes prior (60 seconds * 30). Assuming the table t_sales exists and has been modified within the last 30 minutes, and considering the data_retention_time_in_days is set to 1 day (which enables time travel queries for the past 24 hours), the table t_sales_clone would be successfully created based on the state of t_sales 30 minutes before the clone command was issued.
NEW QUESTION # 193
An Architect has a VPN_ACCESS_LOGS table in the SECURITY_LOGS schema containing timestamps of the connection and disconnection, username of the user, and summary statistics.
What should the Architect do to enable the Snowflake search optimization service on this table?
Answer: B
NEW QUESTION # 194
What considerations need to be taken when using database cloning as a tool for data lifecycle management in a development environment? (Select TWO).
Answer: B,D
NEW QUESTION # 195
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