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Guide DEA-C01 Torrent, DEA-C01 Practice Mock

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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

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 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

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.

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Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q17-Q22):

NEW QUESTION # 17
Steven created the task, what additional privileges required by Steven on the task so that he can suspend or resume the tasks?

A. Steven must have SUSPEND privilege on the task so that he can suspend or resume the task.
B. In addition to the task owner, a Steven Role must have OPERATE privilege on the task so that he can suspend or resume the task.
C. Steven needs to have Global Managed RESUME privilege by TASK administrator.
D. Steven is already owner of the task; he can execute the task & suspend/resume the task without any additional privileges.

Answer: B

Explanation:
Explanation
In addition to the task ownership privilege, a role that has the OPERATE privilege on the task can suspend or resume the task.

NEW QUESTION # 18
What is a characteristic of the use of binding variables in JavaScript stored procedures in Snowflake?

A. Users are restricted from binding JavaScript variables because they create SQL injection attack vulnerabilities
B. All types of JavaScript variables can be bound
C. Only JavaScript variables of type number, string and sf Date can be bound
D. All Snowflake first-class objects can be bound

Answer: C

Explanation:
Explanation
A characteristic of the use of binding variables in JavaScript stored procedures in Snowflake is that only JavaScript variables of type number, string and sf Date can be bound. Binding variables are a way to pass values from JavaScript variables to SQL statements within a stored procedure. Binding variables can improve the security and performance of the stored procedure by preventing SQL injection attacks and reducing the parsing overhead. However, not all types of JavaScript variables can be bound. Only the primitive types number and string, and the Snowflake-specific type sf Date, can be bound. The other options are incorrect because they do not describe a characteristic of the use of binding variables in JavaScript stored procedures in Snowflake. Option A is incorrect because authenticator is not a type of JavaScript variable, but a parameter of the snowflake.connector.connect function. Option B is incorrect because arrow_number_to_decimal is not a type of JavaScript variable, but a parameter of the snowflake.connector.connect function. Option D is incorrect because users are not restricted from binding JavaScript variables, but encouraged to do so.

NEW QUESTION # 19
To support Time Travel, Which of the following SQL extensions/parameters/commands have been implemented?

A. UNDROP command for tables, schemas, and databases.
B. OFFSET (time difference in seconds from the present time)
C. STATEMENT (identifier for statement, e.g. query ID)
D. STATEMENT_ID (identifier for statement, e.g. query ID)
E. AT | BEFORE clause which can be specified in the CREATE ... CLONE commands.
F. ONSET (time difference in seconds from the present time)

Answer: A,B,C,E

NEW QUESTION # 20
A data engineer must ingest a source of structured data that is in .csv format into an Amazon S3 data lake. The .csv files contain 15 columns. Data analysts need to run Amazon Athena queries on one or two columns of the dataset. The data analysts rarely query the entire file.
Which solution will meet these requirements MOST cost-effectively?

A. Create an AWS Glue extract, transform, and load (ETL) job to read from the .csv structured data source. Configure the job to write the data into the data lake in Apache Parquet format.
B. Create an AWS Glue extract, transform, and load (ETL) job to read from the .csv structured data source. Configure the job to ingest the data into the data lake in JSON format.
C. Use an AWS Glue PySpark job to ingest the source data into the data lake in .csv format.
D. Use an AWS Glue PySpark job to ingest the source data into the data lake in Apache Avro format.

Answer: A

NEW QUESTION # 21
A company has multiple applications that use datasets that are stored in an Amazon S3 bucket.
The company has an ecommerce application that generates a dataset that contains personally identifiable information (PII). The company has an internal analytics application that does not require access to the PII.
To comply with regulations, the company must not share PII unnecessarily. A data engineer needs to implement a solution that with redact PII dynamically, based on the needs of each application that accesses the dataset.
Which solution will meet the requirements with the LEAST operational overhead?

A. Create an S3 Object Lambda endpoint. Use the S3 Object Lambda endpoint to read data from the S3 bucket. Implement redaction logic within an S3 Object Lambda function to dynamically redact PII based on the needs of each application that accesses the data.
B. Use AWS Glue to transform the data for each application. Create multiple copies of the dataset.
Give each dataset copy the appropriate level of redaction for the needs of the application that accesses the copy.
C. Create an S3 bucket policy to limit the access each application has. Create multiple copies of the dataset. Give each dataset copy the appropriate level of redaction for the needs of the application that accesses the copy.
D. Create an API Gateway endpoint that has custom authorizers. Use the API Gateway endpoint to read data from the S3 bucket. Initiate a REST API call to dynamically redact PII based on the needs of each application that accesses the data.

Answer: A

Explanation:
Amazon S3 Object Lambda allows you to add your own code to S3 GET requests to modify and process data as it is returned to an application. For example, you could use an S3 Object Lambda to dynamically redact personally identifiable information (PII) from data retrieved from S3. This would allow you to control access to sensitive information based on the needs of different applications, without having to create and manage multiple copies of your data.

NEW QUESTION # 22
......

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