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DEA-C02 Questions Answers - DEA-C02 Exam Brain Dumps

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Snowflake SnowPro Advanced: Data Engineer (DEA-C02) Sample Questions (Q198-Q203):

NEW QUESTION # 198
A Snowflake Data Engineer is tasked with identifying all downstream dependencies of a view named 'CUSTOMER SUMMARY. This view is used by multiple dashboards and reports. They want to use SQL to efficiently find all tables and views that directly depend on 'CUSTOMER SUMMARY. Which of the following SQL queries against the ACCOUNT USAGE schema is the MOST efficient and accurate way to achieve this?

A. Option E
B. Option B
C. Option C
D. Option D
E. Option A

Answer: B

Explanation:
The view in the ACCOUNT_USAGE schema is specifically designed to track object dependencies. option B directly queries this view using the and to find objects that depend on the 'CUSTOMER_SUMMARY view. Options A and C rely on parsing 'QUERY_TEXT , which is less reliable and can lead to false positives or misses. Option D looks for base object which has the opposite meaning of finding dependancies on a target view. Option E finds the OBJECT_ID for the view and is unnecessary and introduces an extra step.

NEW QUESTION # 199
Consider the following Snowflake Javascript UDF designed to convert temperatures between Celsius and Fahrenheit:

Which statement regarding the UDF's security and behavior is MOST accurate?

A. The UDF will always return a value, even if the input 'unit is invalid, due to the implicit type conversion in JavaScript.
B. While the ' SECURE keyword hides the UDF's source code from users without sufficient privileges, users with the ACCOUNTADMIN role can still view the source code.
C. The 'SECURE' keyword ensures that the UDF's code is completely hidden from all users, including those with the ACCOUNTADMIN role.
D. The UDF is vulnerable to SQL injection because the 'unit' parameter is not validated against a predefined list of acceptable values.
E. The UDF is not vulnerable to SQL injection because Javascript UDFs in Snowflake are sandboxed and prevent direct SQL execution.

Answer: E

Explanation:
JavaScript UDFs in Snowflake are sandboxed, preventing SQL injection vulnerabilities. The SECURE keyword hides the UDF definition from users without appropriate privileges, but not from users with sufficient privileges like ACCOUNTADMIN. The UDF explicitly returns NULL for invalid unit values.

NEW QUESTION # 200
A data engineering team is running a series of complex analytical queries against a large Snowflake table. They notice that query performance is inconsistent, with some queries running much slower than others. After investigation, they determine that the queries are not properly leveraging the data clustering. Which of the following actions could improve the query performance related to the data clustering? Select all that apply.

A. Execute SYSTEM$CLUSTERING INFORMATION( ' )' y to assess the impact of clustering on query performance and determine if re-clustering is needed.
B. Increase the virtual warehouse size to improve the performance of all queries, regardless of clustering.
C. Run 'ALTER TABLE DROP CLUSTERING KEY to remove the existing clustering key and allow Snowflake to automatically cluster the data.
D. Run 'SHOW TABLES LIKE ' ' and review the 'clustering_information' column to understand the current clustering depth and benefit.
E. Run 'ALTER TABLE CLUSTER BY (columnl, column2Y to explicitly define a clustering key on the table.

Answer: A,D,E

Explanation:
Option A is correct because explicitly defining a clustering key allows Snowflake to optimize data organization for common query patterns. Option C is correct because understanding the current clustering state helps diagnose if clustering is effective. Option E is correct, using SYSTEM$CLUSTERING INFORMATION is a crucial method to determine reclustering needs. Option B can worsen performance, especially if the automatic clustering does not align with common query patterns. Option D may improve performance to a small extend but doesn't directly address the clustering issue.

NEW QUESTION # 201
You need to load data from a stream of CSV files into a Snowflake table. The CSV files are delivered to an AWS S3 bucket and contain header rows. The files occasionally include records where a text field contains a delimiter character (comma) within the text itself, but these fields are properly enclosed within double quotes. You want to create a file format object that correctly handles the data, including quoted delimiters, and skips the header row. Which of the following file format options are required to achieve this? (Choose two)

A. FIELD OPTIONALLY ENCLOSED BY =
B. ERROR ON COLUMN COUNT MISMATCH = FALSE
C. FILE_FORMAT = (TYPE = CSV)
D. SKIP HEADER = 1
E. FIELD DELIMITER = ','

Answer: A,D

Explanation:
To correctly handle the CSV files with quoted delimiters and skip the header row, you need the following options: 'FIELD OPTIONALLY ENCLOSED BY ='''' specifies that fields can be optionally enclosed by double quotes, allowing delimiters within the text. 'SKIP HEADER = 1' instructs Snowflake to skip the first row (header row) in each file. Other options are implicit by default. A is already set by default, D is for creating a file format object (which it isn't), E is unrelated to skipping header

NEW QUESTION # 202
You are creating a Snowflake Listing to share data with multiple consumers. One consumer requires access to the complete dataset while other consumers need access to a subset of the data based on geographical region (e.g., only data related to the 'US'). You want to minimize data duplication and management overhead. Select all the valid ways to implement this using Snowflake Data Sharing features.

A. Share the base tables in the Listing and instruct each consumer to filter the data based on their region using a WHERE clause.
B. Create multiple secure views, each filtered by region, and create a single Listing that shares all views. Grant access to the appropriate view based on the consumer's region.
C. Share the base tables in the Listing and use Row Access Policies to filter data based on region for specific consumers and allow full access to the entire dataset for the consumer requiring full access. Monitor usage through Snowflake's account usage views.
D. Create multiple Listings, one for each region and one for the complete dataset.

Answer: C

Explanation:
Row Access Policies is the most efficient method because it enables fine-grained access control on the underlying data without creating separate datasets. Option A requires data duplication. Option B is less secure because it relies on the consumer to implement the filtering. Option D creates an overhead by creating multiple Views, and is hard to maintain with changing consumers. Option E hides the data access using a stored procedure, reducing the benefits of data sharing through direct access.

NEW QUESTION # 203
......

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