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Snowflake DEA-C01 Exam Syllabus Topics:

Topic	Details
Topic 1	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 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	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.

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Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q120-Q125):

NEW QUESTION # 120
Ira a Data Engineer with TESLA IT systems, looking out to Compare Traditional Partitioning vs Snowflake micro-partitions for one of the Snowflake Project implementations. Which one of the following is incorrect understanding of Ira about Micro Partitioning?

A. The micro-partition metadata maintained by Snowflake enables precise pruning of col-umns in micro-partitions at query run-time, including columns containing semi-structured data.
B. All DML operations (e.g. DELETE, UPDATE, MERGE) take advantage of the under-lying micro-partition metadata to facilitate and simplify table maintenance.
C. Snowflake stores metadata about all rows stored in a micro-partition, including number of distinct columns.
D. In Snowflake, as data is inserted/loaded into a table, clustering metadata is collected and recorded for each micro-partition created during the process.
E. All data in Snowflake tables is automatically divided into micro-partitions, which are contiguous units of storage compared to traditional partitioning where specialized DDL required.

Answer: C

Explanation:
Explanation
What are Micro-partitions?
All data in Snowflake tables is automatically divided into micro-partitions, which are contiguous units of storage. Each micro-partition contains between 50 MB and 500 MB of uncompressed data (note that the actual size in Snowflake is smaller because data is always stored compressed). Groups of rows in tables are mapped into individual micro-partitions, organized in a columnar fashion. This size and structure allow for extremely granular pruning of very large tables, which can be comprised of millions, or even hundreds of millions, of micro-partitions.
Snowflake stores metadata about all rows stored in a micro-partition, including:
The range of values for each of the columns in the micro-partition.
The number of distinct values.
Additional properties used for both optimization and efficient query processing.
It Never stores number of columns as part of Metadata.
Rest of the statements are correct.

NEW QUESTION # 121
A company receives call logs as Amazon S3 objects that contain sensitive customer information.
The company must protect the S3 objects by using encryption. The company must also use encryption keys that only specific employees can access.
Which solution will meet these requirements with the LEAST effort?

A. Use an AWS CloudHSM cluster to store the encryption keys. Configure the process that writes to Amazon S3 to make calls to CloudHSM to encrypt and decrypt the objects. Deploy an IAM policy that restricts access to the CloudHSM cluster.
B. Use server-side encryption with AWS KMS keys (SSE-KMS) to encrypt the objects that contain customer information. Configure an IAM policy that restricts access to the KMS keys that encrypt the objects.
C. Use server-side encryption with customer-provided keys (SSE-C) to encrypt the objects that contain customer information. Restrict access to the keys that encrypt the objects.
D. Use server-side encryption with Amazon S3 managed keys (SSE-S3) to encrypt the objects that contain customer information. Configure an IAM policy that restricts access to the Amazon S3 managed keys that encrypt the objects.

Answer: B

NEW QUESTION # 122
A company has a business intelligence platform on AWS. The company uses an AWS Storage Gateway Amazon S3 File Gateway to transfer files from the company's on-premises environment to an Amazon S3 bucket.
A data engineer needs to setup a process that will automatically launch an AWS Glue workflow to run a series of AWS Glue jobs when each file transfer finishes successfully.
Which solution will meet these requirements with the LEAST operational overhead?

A. Set up an Amazon EventBridge event that initiates the AWS Glue workflow after every successful S3 File Gateway file transfer event.
B. Set up an AWS Lambda function that will invoke the AWS Glue Workflow. Set up an event for the creation of an S3 object as a trigger for the Lambda function.
C. Set up an on-demand AWS Glue workflow so that the data engineer can start the AWS Glue workflow when each file transfer is complete.
D. Determine when the file transfers usually finish based on previous successful file transfers. Set up an Amazon EventBridge scheduled event to initiate the AWS Glue jobs at that time of day.

Answer: A

Explanation:
Using EventBridge directly to trigger the AWS Glue workflow upon S3 events is straightforward and leverages AWS's event-driven architecture, requiring minimal maintenance.

NEW QUESTION # 123
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 latest version in the GlueVersion field in the Glue job properties.
B. Use the Spot Instance type in Glue job properties.
C. Choose the FLEX execution class in the Glue job properties.
D. Choose the STANDARD execution class in the Glue job properties.

Answer: C

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 # 124
A data engineer wants to improve the performance of SQL queries in Amazon Athena that run against a sales data table.
The data engineer wants to understand the execution plan of a specific SQL statement. The data engineer also wants to see the computational cost of each operation in a SQL query.
Which statement does the data engineer need to run to meet these requirements?

A. EXPLAIN ANALYZE FROM sales;
B. EXPLAIN ANALYZE SELECT * FROM sales;
C. EXPLAIN SELECT * FROM sales;
D. EXPLAIN FROM sales;

Answer: B

Explanation:
https://docs.aws.amazon.com/athena/latest/ug/athena-explain-statement.html

NEW QUESTION # 125
......

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Samuel Ramirez Samuel Ramirez

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Samuel Ramirez Samuel Ramirez

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DEA-C01 Quiz, DEA-C01 Latest Dumps Free

Snowflake DEA-C01 Exam Syllabus Topics:

DEA-C01 Latest Dumps Free - Latest DEA-C01 Test Format

Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q120-Q125):

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