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Snowflake DEA-C01 Exam Syllabus Topics:

Topic	Details
Topic 1	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 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 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 4	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 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.

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Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q82-Q87):

NEW QUESTION # 82
A data engineer needs to schedule a workflow that runs a set of AWS Glue jobs every day. The data engineer does not require the Glue jobs to run or finish at a specific time.
Which solution will run the Glue jobs in the MOST cost-effective way?

A. Choose the FLEX execution class in the Glue job properties.
B. Choose the STANDARD execution class in the Glue job properties.
C. Choose the latest version in the GlueVersion field in the Glue job properties.
D. Use the Spot Instance type in Glue job properties.

Answer: A

Explanation:
Flex allows you to optimize your costs on your non-urgent or non-time sensitive data integration workloads such as testing, and one-time data loads. With Flex, AWS Glue jobs run on spare compute capacity instead of dedicated hardware. The start and runtimes of jobs using Flex can vary because spare compute resources aren't readily available and can be reclaimed during the run of a job.
https://aws.amazon.com/blogs/big-data/introducing-aws-glue-flex-jobs-cost-savings-on-etl- workloads/

NEW QUESTION # 83
A company is setting up a new Amazon SageMaker Unified Studio domain. Each of the company's business units needs isolated control over its own assets, projects, and metadata.
Specific datasets must be shareable with other business units upon approval. The company also requires centralized user authentication and identity mapping. Which solution will meet these requirements?

A. Configure business units to be represented as separate domains. Establish isolated environments with no shared administrative policies. Configure AWS IAM Identity Center for centralized authentication. Delegate administration at the domain level.
B. Configure each business unit as a separate domain unit to manage permissions on assets, projects, and metadata. Configure AWS IAM Identity Center for centralized authentication. Map user profiles to their respective domain units. Enable cross-business unit sharing through access requests. Instruct domain unit owners to approve or deny the requests.
C. Configure business units as separate domain units with owner permissions. Restrict projects exclusively to owners to prevent data sharing between domains. Configure AWS IAM Identity Center for centralized authentication. Map user profiles to their respective domain units.
D. Configure each business unit as a domain unit with delegated ownership and fine-grained permissions policies. Give users the ability to share assets across domain units with explicit access control. Assign API keys to users for authentication to access the domain portal.

Answer: B

Explanation:
SageMaker Unified Studio supports domain units within a single domain to provide isolation of assets, projects, and metadata while still allowing controlled sharing between units. Using AWS IAM Identity Center provides centralized authentication and identity mapping. Cross-unit sharing with approval workflows ensures datasets can be shared securely while maintaining isolation and least privilege.

NEW QUESTION # 84
A Data Engineer is implementing a near real-time ingestionpipeline to toad data into Snowflake using the Snowflake Kafka connector. There will be three Kafka topics created.
......snowflake objects are created automatically when the Kafka connector starts? (Select THREE)

A. Tables
B. Pipes
C. Tasks
D. internal stages
E. External stages
F. Materialized views

Answer: A,B,D

Explanation:
Explanation
The Snowflake objects that are created automatically when the Kafka connector starts are tables, pipes, and internal stages. The Kafka connector will create one table, one pipe, and oneinternal stage for each Kafka topic that is configured in the connector properties. The table will store the data from the Kafka topic, the pipe will load the data from the stage to the table using COPY statements, and the internal stage will store the files that are produced by the Kafka connector using PUT commands. The other options are not Snowflake objects that are created automatically when the Kafka connector starts. Option B, tasks, are objects that can execute SQL statements on a schedule without requiring a warehouse. Option E, external stages, are objects that can reference locations outside of Snowflake, such as cloud storage services. Option F, materialized views, are objects that can store the precomputed results of a query and refresh them periodically.

NEW QUESTION # 85
A data engineer is writing a query to join two tables in Amazon Athena. The data engineer needs to choose the correct join order for the tables to optimize query performance. Which solution will meet these requirements?

A. Specify the larger table on the left side of the join and the smaller table on the right side of the join.
B. Use table statistics to automatically determine the join order.
C. Use AWS Glue to pre-process the tables before performing the join.
D. Specify the smaller table on the left side of the join and the larger table on the right side of the join.

Answer: D

Explanation:
Amazon Athena (based on Presto/Trino) performs joins more efficiently when the smaller table is placed on the left side because it is used as the build side of the join and can be loaded into memory. This minimizes data shuffling and improves performance when joining with a larger table on the right side.

NEW QUESTION # 86
Alex, a Data Engineer with one of the Data analytics Organization, created the Materialized view over External tables to improve Data Reporting Experience.
Step 1: He created materialized view named DataReportMV
1.create or replace materialized view DataReportMV as
2.select Item_id, Item_price from Items;
Step 2: He joined a materialized view with a sales table as
1.create or replace view Revenue as
2.select m.item_id, sum(ifnull(s.quantity, 0)) as quantity,
3.sum(ifnull(quantity * (s.price - m.item_price), 0)) as profit
4.from DataReportMV as m left outer join sales as s on s.item_id = m.item_id
5.group by m.item_id;
Step 3: After 1 hour, he decided to temporarily suspend the use (and maintenance) of the DataRe-portMV materialized view for cost saving purpose.
alter materialized view DataReportMV suspend;
Please select what Alex is doing wrong here?

A. Alex is doing everything correct.
B. Once DataReportMV got suspended , any query on the top of the view will generate er-ror like:
Failure during expansion of view 'DATAREPORTMV': SQL compilation error: Material-ized view DataReportMV is invalid.
C. A materialized view, DataReportMV does not support Join operations, so Step 2 would be failed & he cannot proceed further.
D. There is no command like suspend for temporarily suspension of Materialized views, Step 3 will give error like invalid Suspend command.
E. Materialized view on top of External tables is not supported feature.

Answer: A

Explanation:
Explanation
All Steps will be executed successfully by Alex without any error.

NEW QUESTION # 87
......

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