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Snowflake DEA-C01 Exam Syllabus Topics:

Topic	Details
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	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	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.

Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q89-Q94):

NEW QUESTION # 89
A company stores petabytes of data in thousands of Amazon S3 buckets in the S3 Standard storage class. The data supports analytics workloads that have unpredictable and variable data access patterns.
The company does not access some data for months. However, the company must be able to retrieve all data within milliseconds. The company needs to optimize S3 storage costs.
Which solution will meet these requirements with the LEAST operational overhead?

A. Use S3 Intelligent-Tiering. Activate the Deep Archive Access tier.
B. Use S3 Intelligent-Tiering. Use the default access tier.
C. Use S3 Storage Lens activity metrics to identify S3 buckets that the company accesses infrequently. Configure S3 Lifecycle rules to move objects from S3 Standard to the S3 Standard- Infrequent Access (S3 Standard-IA) and S3 Glacier storage classes based on the age of the data.
D. Use S3 Storage Lens standard metrics to determine when to move objects to more cost- optimized storage classes. Create S3 Lifecycle policies for the S3 buckets to move objects to cost-optimized storage classes. Continue to refine the S3 Lifecycle policies in the future to optimize storage costs.

Answer: B

NEW QUESTION # 90
To troubleshoot data load failure in one of your Copy Statement, Data Engineer have Executed a COPY statement with the VALIDATION_MODE copy option set to RETURN_ALL_ERRORS with reference to the set of files he had attempted to load. Which below function can facilitate analysis of the problematic records on top of the Results produced? [Select 2]

A. Rejected_record
B. RESULT_SCAN
C. LOAD_ERROR
D. LAST_QUERY_ID

Answer: B,D

Explanation:
Explanation
LAST_QUERY_ID() Function
Returns the ID of a specified query in the current session. If no query is specified, the most recently executed query is returned.
RESULT_SCAN() Function
Returns the result set of a previous command (within 24 hours of when you executed the query) as if the result was a table.
The following example validates a set of files (SFfile.csv.gz) that contain errors. To facilitate analy-sis of the errors, a COPY INTO <location> statement then unloads the problematic records into a text file so they could be analyzed and fixed in the original data files. The statement queries the RESULT_SCAN table.
1.#copy into Snowtable
2.from @SFstage/SFfile.csv.gz
3.validation_mode=return_all_errors;
4.#set qid=last_query_id();
5.#copy into @SFstage/errors/load_errors.txt from (select rejected_record from ta-ble(result_scan($qid))); Note: Other options are not valid functions.

NEW QUESTION # 91
A company uses Apache Airflow to orchestrate the company's current on-premises data pipelines. The company runs SQL data quality check tasks as part of the pipelines. The company wants to migrate the pipelines to AWS and to use AWS managed services.
Which solution will meet these requirements with the LEAST amount of refactoring?

A. Convert the pipelines to AWS Step Functions workflows. Recreate the data quality checks in SQL as Python based AWS Lambda functions.
B. Migrate the existing Airflow orchestration configuration into Amazon Managed Workflows for Apache Airflow (Amazon MWAA). Create the data quality checks during the ingestion to validate the data quality by using SQL tasks in Airflow.
C. Setup AWS Outposts in the AWS Region that is nearest to the location where the company uses Airflow. Migrate the servers into Outposts hosted Amazon EC2 instances. Update the pipelines to interact with the Outposts hosted EC2 instances instead of the on-premises pipelines.
D. Create a custom Amazon Machine Image (AMI) that contains the Airflow application and the code that the company needs to migrate. Use the custom AMI to deploy Amazon EC2 instances.
Update the network connections to interact with the newly deployed EC2 instances.

Answer: B

Explanation:
Amazon MWAA is a managed service for running Apache Airflow. It allows migrating existing Airflow configurations with minimal changes. Data quality checks can continue to be implemented as SQL tasks in Airflow, similar to the current setup.

NEW QUESTION # 92
A Data Engineer is writing a Python script using the Snowflake Connector for Python. The Engineer will use the snowflake. Connector.connect function to connect to Snowflake The requirementsare:
*Raise an exception if the specified database schema or warehouse does not exist
*improve download performance
Whichparameters of the connect function should be used? (Select TWO).

A. arrow_nunber_to_decimal
B. validate_default_parameters
C. client_prefetch_threads
D. client_session_keep_alivs
E. authenticator

Answer: B,C

Explanation:
Explanation
The parameters of the connect function that should be used are client_prefetch_threads and validate_default_parameters. The client_prefetch_threads parameter controls the number of threads used to download query results from Snowflake. Increasing this parameter can improve download performance by parallelizing the download process. The validate_default_parameters parameter controls whether an exception should be raised if the specified database, schema, or warehouse does not exist or is not authorized. Setting this parameter to True can help catch errors early and avoid unexpected results.

NEW QUESTION # 93
How can the following relational data be transformed into semi-structured data using the LEAST amount of operational overhead?

A. Use the OBJECT_CONSTRUCT function to return a Snowflake object
B. Use the TO_VARIANT function to convert each of the relational columns to VARIANT.
C. Use the PAESE_JSON function to produce a variant value
D. Use the to_json function

Answer: A

Explanation:
Explanation
This option is the best way to transform relational data into semi-structured data using the least amount of operational overhead. The OBJECT_CONSTRUCT function takes a variable number of key-value pairs as arguments and returns a Snowflake object, which is a variant type that can store JSON data. The function can be used to convert each row of relational data into a JSON object with the column names as keys and the column values as values.

NEW QUESTION # 94
......

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Free Download DEA-C01 Exam Answers - How to Download for DEA-C01 Latest Practice Questions Free of Charge

DEA-C01 Latest Practice Questions | Reliable DEA-C01 Exam Materials

Snowflake DEA-C01 Exam Syllabus Topics:

Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q89-Q94):

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