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Snowflake DEA-C01 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • 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.
Topic 3
  • 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 4
  • 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 5
  • 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.

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Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q30-Q35):

NEW QUESTION # 30
A financial services company stores financial data in Amazon Redshift. A data engineer wants to run real-time queries on the financial data to support a web-based trading application. The data engineer wants to run the queries from within the trading application.
Which solution will meet these requirements with the LEAST operational overhead?

Answer: C

Explanation:
https://docs.aws.amazon.com/redshift/latest/mgmt/data-api.html


NEW QUESTION # 31
Which are supported Programming Languages for Creating UDTFs?

Answer: A,C,E


NEW QUESTION # 32
A company uses an Amazon RDS for Oracle database to store data for an ecommerce application. The company needs a solution to make the data in all tables available for future analytics. The solution must process data from a table named customer_complaints in near real time by using a REST API.
Which solution will meet these requirements MOST cost-effectively?

Answer: B

Explanation:
AWS DMS can stream change data from the Oracle customer_complaints table to Kinesis Data Streams for near real-time processing by a Lambda that calls the REST API, while a separate DMS task delivers all tables to Amazon S3 for future analytics. This achieves both streaming and batch needs with minimal infrastructure and cost.


NEW QUESTION # 33
An insurance company stores transaction data that the company compressed with gzip.
The company needs to query the transaction data for occasional audits.
Which solution will meet this requirement in the MOST cost-effective way?

Answer: C


NEW QUESTION # 34
Which Snowflake objects does the Snowflake Kafka connector use? (Select THREE).

Answer: A,C,D

Explanation:
Explanation
The Snowflake Kafka connector uses three Snowflake objects: pipe, internal table stage, and internal named stage. The pipe object is used to load data from an external stage into a Snowflake table using COPY statements. The internal table stage is used to store files that are loaded from Kafka topics into Snowflake using PUT commands. The internal named stage is used to store files that are rejected by the COPY statements due to errors or invalid data. The other options are not objects that are used by the Snowflake Kafka connector.
Option B, serverless task, is an object that can execute SQL statements on a schedule without requiring a warehouse. Option C, internal user stage, is an object that can store files for a specific user in Snowflake using PUT commands. Option F, storage integration, is an object that can enable secure access to external cloud storage services without exposing credentials.


NEW QUESTION # 35
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