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Snowflake DEA-C02 Exam Syllabus Topics:

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

1. 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 C
C) Option B
D) Option A
E) Option D

2. You have a Snowflake table, 'CUSTOMER ORDERS', with columns like 'CUSTOMER ID', 'ORDER DATE', 'ORDER AMOUNT', and 'REGION'. A Bl dashboard relies on a query that aggregates data from this table, but the query performance is consistently slow. The query frequently filters by 'ORDER DATE and groups by 'REGION'. Based on the following 'EXPLAIN' output, which combination of techniques should be considered to improve the performance the most?

A) Increase the virtual warehouse size to 'LARGE or 'XLARGE.
B) Cluster the 'CUSTOMER ORDERS table on 'ORDER DATE' and 'REGION'.
C) Redesign the dashboard to minimize the data being displayed at once to the user.
D) Create a materialized view that pre-aggregates the data by 'ORDER DATE and 'REGION'
E) Create an index on the 'ORDER DATE column.

3. You are tasked with creating a JavaScript UDF in Snowflake to parse JSON data containing nested arrays of objects. The UDF needs to extract specific values from these nested objects and return them as a comma-separated string. Given the JSON structure below, and the requirement to extract the 'value' field from each object within the 'items' array located inside each element of the 'data' array, which of the following JavaScript UDF definitions will correctly achieve this, assuming the input JSON is passed as a string?

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

4. You have a VARIANT column named 'raw_data' in a Snowflake table 'eventS , containing nested JSON data'. You need to extract specific fields Cevent_id', 'timestamp' , and 'user.user_id') and load them into a relational table 'structured_events' with columns 'event_id' , 'timestamp' , and 'user_id', respectively. However, some entries may be missing the 'user' object. Which of the following SQL statements will achieve this while handling missing 'user' objects gracefully and ensuring data integrity, and also efficiently handle potentially large JSON payloads?

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

5. You are tasked with designing a solution to ingest a continuous stream of unstructured log data from various sources into Snowflake. The log data includes text, JSON, and XML formats. The goal is to efficiently store the data, allow for flexible querying, and minimize storage costs. Which of the following approaches would BEST address these requirements? (Select TWO)

A) Ingest all data 'as is' into a raw staging table. Then create a Task that use Python UDF to parse data and save it to different tables as required
B) Use Snowflake's external functions to parse the log data during query execution.
C) Pre-process the log data to convert all formats into a standardized JSON format before ingestion.
D) Ingest all log data into a single VARIANT column in a Snowflake table.
E) Create separate tables for each log data format (text, JSON, XML).

Solutions: