Snowflake DEA-C02 : 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. A data team is using Snowflake to analyze sensor data from thousands of IoT devices. The data is ingested into a table named 'SENSOR READINGS' which contains columns like 'DEVICE ID', 'TIMESTAMP', 'TEMPERATURE', 'PRESSURE', and 'LOCATION' (a GEOGRAPHY object). Analysts frequently run queries that calculate the average temperature and pressure for devices within a specific geographic area over a given time period. These queries are slow, especially when querying data from multiple months. Which of the following approaches, when combined, will BEST optimize the performance of these queries using the query acceleration service?

A) Enable Automatic Clustering on 'DEVICE_ID' , then enable query acceleration on the virtual warehouse.
B) Cluster the table by 'LOCATION' and 'TIMESTAMP , and enable search optimization on the 'LOCATION' column, and then enable query acceleration.
C) Enable search optimization on 'TEMPERATURE and 'PRESSURE columns and enable query acceleration.
D) Create a materialized view that pre-calculates the average temperature and pressure by device and location. Then enable query acceleration on the virtual warehouse.
E) Partition the ' SENSOR_READINGS table by 'TIMESTAMP (e.g., daily partitions). Enable search optimization on the 'LOCATION' column and enable query acceleration.

2. A global e-commerce company, 'GlobalMart', uses Snowflake for its data warehousing needs. They operate primarily in the US (us-east-1) and Europe (eu-west-l). They're implementing cross-region replication for disaster recovery and business continuity. Their requirements are: 1) All data from the US region needs to be replicated to the EU region. 2) The failover to the EU region should have minimal downtime. 3) Replication should be automatic and continuous. Considering these requirements, which of the following Snowflake features and configurations would be the MOST suitable and efficient?

A) Manually unload data from the US region and load it into the EU region using SnowSQL. Automate this process using a scheduled task.
B) Create a database replica in the EU region and manually refresh it periodically using 'CREATE DATABASE AS CLONE'
C) Use Snowflake's Data Sharing feature to share data from the US region with an account in the EU region. This automatically replicates the data.
D) Enable database replication using replication groups, configure a primary database in us-east-I , and a secondary database in eu-west-l. Set the replication schedule with 'ALTER REPLICATION GROUP ADD .
E) Export data from the US region to cloud storage (e.g., AWS S3 or Azure Blob Storage) and then load it into the EU region using Snowpipe.

3. You are tasked with optimizing the performance of a Snowflake virtual warehouse used for running several types of queries: short- running analytical queries with strict latency requirements, long-running batch data transformations, and ad-hoc queries from data scientists. The workload is unpredictable, and the team wants to minimize queueing and maximize resource utilization. Which warehouse configuration would be MOST appropriate to handle this mixed workload, minimizing cost and maximizing performance?

A) A single Small warehouse with auto-suspend set to 60 minutes.
B) A single X-Large warehouse with auto-suspend set to 5 minutes.
C) A multi-cluster warehouse with a scaling policy of 'Economy' and a minimum of 1 and maximum of 2 clusters with auto-suspend set to 5 minutes.
D) A multi-cluster warehouse with a scaling policy of 'Standard' and a minimum of 1 and maximum of 3 clusters with auto-suspend set to 10 minutes.
E) Three separate warehouses: a Medium warehouse for analytical queries, a Large warehouse for batch transformations, and an X-Small warehouse for ad-hoc queries.

4. You accidentally truncated a large table named 'SALES DATA' in your 'REPORTING DB" database. You realize this happened 2 days ago, and your account has the default Time Travel retention of 1 day. You need to recover this table with minimal downtime. Analyze the situation and determine the best course of action, considering cost and recovery time.

A) Immediately contact Snowflake Support to initiate a restore from Fail-safe, understanding that this process may take several hours or even days.
B) Raise a support ticket requesting data recovery from failsafe. Since data retention period has expired.
C) Because the data retention period has expired, the table is unrecoverable using Snowflake's built-in features; you must restore from an external backup solution if available.
D) Increase the account-level to 2 days and then use the UNDROP TABLE SALES_DATA' command.
E) Create a clone of the table using the 'AT clause and a timestamp from 1 day ago. This would prevent any additional cost.

5. You are tasked with processing streaming data in Snowflake using Snowpark Python. The raw data arrives in a DataFrame raw events' with the following schema: 'event id: string', 'event_time: timestamp', 'user id: string', and 'event data: string'. You need to perform the following data transformations: 1 . Extract a specific value from the JSON 'event_data' using the 'get' function to find the 'product_id' and create a new column named 'product id' of type STRING. 2. Filter the DataFrame to include only events where the is NOT NULL and the is within the last hour. 3. Aggregate the filtered data to count the number of events per 'product id'. Which of the following code snippets correctly performs these transformations in an efficient and performant manner?

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

Solutions: