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Snowflake DEA-C02 Exam Syllabus Topics:

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

1. You are tasked with optimizing a continuous data pipeline that loads data from an external stage into a Snowflake table using streams.
The pipeline is experiencing significant latency during peak hours. The stream is defined on a very large table with frequent updates and deletes. Which of the following strategies would be MOST effective in reducing the latency of the data pipeline, considering stream performance and cost implications?

A) Increase the size of the virtual warehouse used for loading data. This will provide more compute resources for processing the stream.
B) Reduce the RETENTION TIME of the stream. This will limit the amount of historical data tracked and improve performance.
C) Implement a materialized view on top of the stream to pre-aggregate the data.
D) Create multiple streams on the same base table, each filtering for specific types of changes (e.g., INSERT, UPDATE, DELETE).
E) Implement a more aggressive pruning strategy on the base table to reduce the amount of data that the stream needs to track.

2. A data engineering team is building a data pipeline in Snowflake. They are using tasks and streams to incrementally load data into a fact table. The team needs to monitor the pipeline's performance and ensure data lineage. What are the valid and most effective techniques to ensure that this pipeline adheres to compliance and governance rules?

A) Leverage Snowflake's replication features for disaster recovery, monitor only the replication lag, and disable all security policies to improve performance since those tasks have already been validated during the initial deployment of the software.
B) Use Account Usage views like 'TASK HISTORY and 'STREAM_LAG' to track task execution and stream latency, create stored procedures to log metadata about each pipeline run to a separate metadata table, and rely on developers to manually document the pipeline's data flow and policy enforcement.
C) Implement Snowflake's Data Lineage and Object Dependencies features to track data flow automatically, create Alerts based on 'TASK HISTORY to monitor task failures, and enforce data masking and row-level security policies at the table level. Use Snowflake's tags to categorise and classify objects.
D) Use a third-party data catalog to track lineage, monitor task performance via 'TASK_HISTORY, and ignore data masking and row-level security policies for simplicity in the initial implementation.
E) Enable Snowflake Horizon features, which include Data Lineage, Object Dependencies and Discovery and integrate it with the data lake and also tag the data pipeline.

3. You have a table 'SALES DATA' in your production environment. You want to create a development environment using cloning, but only want to include data up to a specific point in time to minimize storage costs and potential exposure of recent, sensitive data'. You know there were significant changes to the 'SALES DATA' table structure on '2024-01-15'. Your goal is to create a clone that only includes the structure as of '2024-01-14'. Which Snowflake command is MOST appropriate for this scenario?

A)

B)

C)

D)

E)

4. You have a large dataset stored in AWS S3 in Parquet format. The data is constantly updated by an external process, but you need to run read-only analytical queries against the most current data in Snowflake without ingesting it. Which approach is the MOST efficient and cost-effective way to achieve this, considering minimal latency for query results?

A) Use Snowpipe to continuously ingest the Parquet files from S3 into a Snowflake table.
B) Create an external table in Snowflake pointing to the S3 location. Configure automatic data refresh using the 'AUTO REFRESH' parameter and a notification integration.
C) Create a Snowflake internal stage, load the Parquet files into the stage periodically, and create a table from the staged files.
D) Create a view on top of the S3 files using a custom Java UDF to read Parquet data directly. Then, query the view.
E) Create a Snowflake external table pointing to the S3 location. Manually refresh the external table metadata periodically using the 'ALTER EXTERNAL TABLE REFRESH' command.

5. You have a Snowflake stage named that points to an S3 bucket containing JSON log files. You want to create a directory table to track the files and their metadata'. The log files are continuously being added to the bucket. Which of the following sets of steps is the MOST efficient way to create and maintain an up-to-date directory table for this stage?

A) Option B
B) Option E
C) Option A
D) Option D
E) Option C

Solutions: