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Snowflake DEA-C02 Exam Syllabus Topics:

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

1. Consider the following Snowflake UDTF definition written in Python:

Which of the following statements are TRUE regarding the deployment and usage of this UDTF?

A) The UDTF will automatically be available in all schemas across all databases in the Snowflake account.
B) The return type of the generator 'yield' must strictly adhere to the declared output schema , or errors will occur during execution.
C) The UDTF can be called directly in SQL using 'SELECT FROM TABLE(process_json(VARlANT COLUMN));' without any prior registration.
D) The library needs to be explicitly installed and configured within the UDTF's environment using a Snowpark session.
E) The UDTF needs to be registered using 'session.udtf.register' or 'create or replace function' with the 'imports' clause referencing the Python file, and the handler' specifying the function name.

2. A data provider wants to share a large dataset (several TB) with multiple consumers. The dataset is updated daily. The provider wants to minimize the cost associated with data sharing and ensure that consumers receive consistent data'. Which of the following strategies would be the MOST cost-effective and maintainable?

A) Create a data share with views that point to the base tables. Use time travel to allow consumers to query data from a specific point in time before the daily update.
B) Create a data share with views that point to the base tables, and clone the base tables daily into a separate 'staging' database before sharing.
C) Create a data share and create a separate database for each consumer, cloning the data into each consumer's database daily.
D) Create a data share and grant access to all consumers directly on the base tables.
E) Create a data share containing external tables pointing to data stored in cloud storage (e.g., AWS S3), updated daily using a pipeline.

3. A data engineer needs to optimize the performance of a series of complex transformations performed using Snowflake stored procedures. These procedures involve multiple table joins, aggregations, and data filtering operations. The current execution time is unacceptably long. Which of the following optimization strategies are most likely to provide the greatest performance improvements, considering both code-level optimizations and Snowflake's architecture? Select all that apply.

A) Implement data caching within the stored procedures using temporary tables to store intermediate results, reducing the need to repeatedly query the same data.
B) Ensure the underlying tables are appropriately clustered and consider using materialized views for frequently accessed aggregations or pre-computed results to improve query performance.
C) Rewrite the stored procedures to use procedural logic (e.g., loops and cursors) more extensively, as this allows for fine-grained control over the execution flow and can improve performance for certain operations.
D) Refactor the stored procedures to leverage set-based operations (e.g., using SQL statements with joins and aggregations) whenever possible, allowing Snowflake to parallelize the execution across multiple nodes.
E) Use external functions written in languages like Python or Java for computationally intensive tasks that are not efficiently handled by SQL, taking advantage of Snowflake's support for external functions.

4. You are designing a Snowflake data pipeline that continuously ingests clickstream dat a. You need to monitor the pipeline for latency and throughput, and trigger notifications if these metrics fall outside acceptable ranges. Which of the following combinations of Snowflake features and techniques would be MOST effective for achieving this goal?

A) Implement a combination of Snowflake Streams, Tasks, and external functions. Streams capture changes, Tasks process the changes, and external functions send notifications to a monitoring service when latency or throughput issues are detected.
B) Use Snowflake's Event Tables and Event Notifications to capture events related to data ingestion and processing. Configure alerts based on event patterns that indicate latency or throughput issues.
C) Rely on Snowflake's default resource monitors to track warehouse usage. If warehouse usage exceeds a certain threshold, assume there are performance issues and send a notification.
D) Use Snowflake's 'QUERY_HISTORY view to track query execution times and implement a scheduled task that queries this view, calculates latency and throughput, and sends email notifications using Snowflake's built-in email integration if thresholds are exceeded.
E) Create a custom dashboard using a Bl tool that connects to Snowflake via JDBC/ODBC and visualizes data ingestion and processing metrics. Manually monitor the dashboard for anomalies.

5. You're designing a data pipeline in Snowflake that utilizes an external function to perform sentiment analysis on customer reviews using a third-party NLP service. This service charges per request. You need to minimize costs while ensuring timely processing of the reviews.
Which of the following strategies would be most effective in optimizing the cost and performance of your external function?

A) Pre-process the customer reviews in Snowflake to filter out irrelevant reviews (e.g., very short reviews or reviews with stop words) before sending them to the external function.
B) Implement rate limiting and error handling in the external service (e.g., AWS Lambda or Azure Function) to gracefully handle API usage limits and prevent excessive charges due to errors.
C) Implement a caching mechanism (e.g., using a Snowflake table or an external cache) to store the sentiment analysis results for frequently occurring reviews or similar text patterns, avoiding redundant API calls.
D) Bypass the external function completely and rely solely on Snowflake's built-in NLP functions for sentiment analysis.
E) Set 'MAX BATCH_ROWS' to a very high value (e.g., 10000) to maximize the number of rows processed per API call, even if it increases latency for individual reviews.

Solutions: