Snowflake DEA-C02 test insides dumps : SnowPro Advanced: Data Engineer (DEA-C02)

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Snowflake DEA-C02 Exam Syllabus Topics:

Snowflake SnowPro Advanced: Data Engineer (DEA-C02) Sample Questions:

1. You are developing a data pipeline that extracts data from an on-premise PostgreSQL database, transforms it, and loads it into Snowflake. You want to use the Snowflake Python connector in conjunction with a secure method for accessing the PostgreSQL database. Which of the following approaches provides the MOST secure and manageable way to handle the PostgreSQL connection credentials in your Python script when deploying to a production environment?

A) Store the PostgreSQL username and password in a configuration file (e.g., JSON or YAML) and load the file in the Python script.
B) Prompt the user for the PostgreSQL username and password each time the script is executed.
C) Store the PostgreSQL username and password in environment variables and retrieve them in the Python script using 'os.environ'
D) Store the PostgreSQL username and password in a dedicated secrets management service (e.g., AWS Secrets Manager, HashiCorp Vault, Azure Key Vault) and retrieve them in the Python script using the appropriate API.
E) Hardcode the PostgreSQL username and password directly into the Python script.

2. You are using Snowpipe to load data from an AWS S3 bucket into Snowflake. The data files are compressed using GZIP and are being delivered frequently. You have observed that the pipe's backlog is increasing and data latency is becoming unacceptable. Which of the following actions could you take to improve Snowpipe's performance? (Select all that apply)

A) Check if the target table has any active clustering keys defined which could be causing slow down
B) Reduce the number of columns in the target Snowflake table. Fewer columns reduce the overhead of data loading.
C) Increase the virtual warehouse size associated with the pipe.
D) Ensure that the S3 event notifications are correctly configured and that there are no errors in the event delivery mechanism.
E) Optimize the file size of the data files in S3. Smaller files are processed faster by Snowpipe.

3. You have a table 'EVENTS' containing application event data with columns 'EVENT ID, 'USER ID, 'EVENT TYPE, and EVENT DETAILS (VARCHAR). The 'EVENT DETAILS column contains comma-separated key-value pairs (e.g., 'location=USA,device=mobile,os=iOS'). Your objective is to transform this structured data into a VARIANT column named EVENT JSON' in a new table 'EVENTS JSON'. The data in EVENT DETAILS has inconsistent key-value pairs across different rows. Which of the following methods are the most efficient and scalable to parse the key-value pairs in 'EVENT DETAILS' and construct the JSON objects?

A) Use 'SPLIT to split the key-value pairs into an array, then use a LATERAL FLATTEN to create rows from array, then use 'SPLIT again to split each row by '='. Finally, construct the JSON using 'OBJECT CONSTRUCT.
B) Use a combination of 'SPLIT, 'REGEXP_REPLACE and 'OBJECT_CONSTRUCT within a user-defined function (UDF) to parse the string and build the JSON object.
C) Use a Java UDF that iterates through the string, splitting it based on commas and equals signs, and then constructs a JSON object using a JSON library.
D) Use only REGEXP EXTRACT ALL' with appropriate regular expressions to extract all keys and values into arrays, then use a JavaScript UDF to combine them into a JSON object.
E) Utilize to split the key-value pairs into rows, then use 'REGEXP_EXTRACT to extract the key and value. Finally, use 'OBJECT_CONSTRUCT and to construct the JSON object.

4. You are designing a data protection strategy for a Snowflake environment that processes sensitive payment card industry (PCI) data'. You decide to use a combination of column-level security and external tokenization. Which of the following statements are TRUE regarding the advantages of using both techniques together? (Select TWO)

A) Tokenization ensures compliance with PCl DSS standards, while masking policies are primarily useful for internal access control and obfuscation for development environments. Using both doesn't increase security.
B) The use of both techniques increases query performance drastically.
C) Masking policies and external tokenization provide independent layers of security. If one is compromised, the other still provides protection.
D) Combining masking policies and external tokenization allows for complete elimination of PCl data from the Snowflake environment, even during processing.
E) Column-level security can be used to restrict access to the tokenization UDF itself, ensuring that only authorized users can perform tokenization or detokenization operations.

5. Which of the following statements are true regarding data masking policies in Snowflake? (Select all that apply)

A) Data masking policies are supported on external tables.
B) Different masking policies cannot be applied to different columns within the same table.
C) The 'CURRENT_ROLE()' function can be used within a masking policy to implement role-based data masking.
D) Data masking policies can be applied to both tables and views.
E) Once a masking policy is applied to a column, the original data is permanently altered.

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