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Snowflake DEA-C01 Exam Syllabus Topics:

Topic	Details
Topic 1	Data Movement: Snowflake Data Engineers and Software Engineers are assessed on their proficiency to load, ingest, and troubleshoot data in Snowflake. It evaluates skills in building continuous data pipelines, configuring connectors, and designing data sharing solutions.
Topic 2	Storage and Data Protection: The topic tests the implementation of data recovery features and the understanding of Snowflake's Time Travel and micro-partitions. Engineers are evaluated on their ability to create new environments through cloning and ensure data protection, highlighting essential skills for maintaining Snowflake data integrity and accessibility.
Topic 3	Data Transformation: The SnowPro Advanced: Data Engineer exam evaluates skills in using User-Defined Functions (UDFs), external functions, and stored procedures. It assesses the ability to handle semi-structured data and utilize Snowpark for transformations. This section ensures Snowflake engineers can effectively transform data within Snowflake environments, critical for data manipulation tasks.
Topic 4	Security: The Security topic of the DEA-C01 test covers the principles of Snowflake security, including the management of system roles and data governance. It measures the ability to secure data and ensure compliance with policies, crucial for maintaining secure data environments for Snowflake Data Engineers and Software Engineers.
Topic 5	Performance Optimization: This topic assesses the ability to optimize and troubleshoot underperforming queries in Snowflake. Candidates must demonstrate knowledge in configuring optimal solutions, utilizing caching, and monitoring data pipelines. It focuses on ensuring engineers can enhance performance based on specific scenarios, crucial for Snowflake Data Engineers and Software Engineers.

Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q22-Q27):

NEW QUESTION # 22
In data modeling, an entity-relationship diagram (ERD) is primarily used to:

A. Transform raw data into structured data.
B. Store data in a physical location.
C. Illustrate relationships between entities.
D. Cleanse dirty data.

Answer: C

NEW QUESTION # 23
Mohan, Data engineer works with ALTUSO Company, wants to programmatically check the status of the query. He needs query id to identify each query executed by Snowflake & using Snowflake Connector for Python to execute a query, how he will be able to meet this requirements. Select the best options you will suggest?

A. Using python connector, snowflake does not support queryID retrieval for both syn-chronous & asynchronous query.
B. He needs to query history views to get the queryID as best practices.
C. When he used the Snowflake Connector for Python to execute a query, he can access the query ID through the pyqueryid attribute in the Cursor object.
D. He can access the query ID through the sfqid attribute in the Cursor object.
1.cur = con.cursor()
2.cur.execute("SELECT * FROM snowtable")
3.print(cur.sfqid)

Answer: D

Explanation:
Explanation
Retrieving the Snowflake Query ID
A query ID identifies each query executed by Snowflake. When you use the Snowflake Connector for Python to execute a query, you can access the query ID through the sfqid attribute in the Cursor object:
1.# Retrieving a Snowflake Query ID
2.cur = con.cursor()
3.cur.execute("SELECT * FROM testtable")
4.print(cur.sfqid)

NEW QUESTION # 24
A manufacturing company has many IoT devices in facilities around the world. The company uses Amazon Kinesis Data Streams to collect data from the devices. The data includes device ID, capture date, measurement type, measurement value, and facility ID. The company uses facility ID as the partition key.
The company's operations team recently observed many WriteThroughputExceeded exceptions.
The operations team found that some shards were heavily used but other shards were generally idle.
How should the company resolve the issues that the operations team observed?

A. Change the partition key from facility ID to a randomly generated key.
B. Archive the data on the producer's side.
C. Increase the number of shards.
D. Change the partition key from facility ID to capture date.

Answer: A

Explanation:
The best solution to resolve the issue of uneven shard usage and WriteThroughputExceeded exceptions is to balance the load more evenly across the shards. This can be effectively achieved by changing the partition key to something that ensures a more uniform distribution of data across the shards.

NEW QUESTION # 25
Which privilege are required on an object (i.e. user or role) with USERADMIN Role can modify the object properties?

A. OWNERSHIP
B. OPEARTE
C. MODIFY
D. MANAGE GRANTS

Answer: A

NEW QUESTION # 26
To help manage STAGE storage costs, Data engineer recommended to monitor stage files and re-move them from the stages once the data has been loaded and the files which are no longer needed. Which option he can choose to remove these files either during data loading or afterwards?

A. He can choose to remove stage files during data loading (using the COPY INTO <table> command).
B. Script can be used during data loading & post data loading with DELETE command.
C. Files no longer needed, can be removed using the PURGE=TRUE command.
D. Files no longer needed, can be removed using the REMOVE command.

Answer: A,C

Explanation:
Explanation
Managing Data Files
Staged files can be deleted from a Snowflake stage (user stage, table stage, or named stage) using the following methods:
Files that were loaded successfully can be deleted from the stage during a load by specifying the PURGE copy option in the COPY INTO <table> command.
After the load completes, use the REMOVE command to remove the files in the stage.
Removing files ensures they aren't inadvertently loaded again. It also improves load performance, because it reduces the number of files that COPY commands must scan to verify whether existing files in a stage were loaded already.

NEW QUESTION # 27
......

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