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

1. A Snowflake data engineer is troubleshooting a performance issue with a query that retrieves data from a large table (TRANSACTIONS). The table has a VARIANT column containing semi-structured JSON data representing transaction details. The query uses several LATERAL FLATTEN functions to extract specific fields from the JSON and filters the data based on these extracted values. Despite having adequate virtual warehouse resources, the query is running slower than expected. Identify the MOST effective strategy to improve the performance of this query:

A) Rewrite the query to use regular expressions instead of LATERAL FLATTEN for extracting the fields from the JSON data.
B) Create a new table with pre-extracted fields from the VARIANT column and use this table in the query instead of the LATERAL FLATTEN operations.
C) Increase the virtual warehouse size to provide more memory for processing the JSON data.
D) Convert the VARIANT column to a VARCHAR column and store the JSON data as a string.
E) Create a search optimization service on the TRANSACTIONS table for the VARIANT column.

2. A financial services company is using Snowflake Streams on a table 'TRANSACTIONS' to capture changes for auditing purposes. The 'TRANSACTIONS' table contains sensitive data, and the auditing team requires the stream to only capture changes to specific columns: 'ACCOUNT ID', 'TRANSACTION DATE', and 'TRANSACTION AMOUNT'. Which of the following approaches is the MOST efficient and secure way to achieve this requirement, ensuring minimal performance impact and data exposure?

A) Create a standard Stream on the 'TRANSACTIONS table and then filter the results in downstream processing to only include the required columns.
B) Create a Stream on the 'TRANSACTIONS' table. Periodically truncate stream and reload all data from TRANSACTION table by applying filter while loading.
C) Create a View that selects only the 'ACCOUNT ID, 'TRANSACTION DATE, and 'TRANSACTION AMOUNT columns and create a Stream on the View.
D) Create a task that clones the TRANSACTIONS table and a stream on that cloned table, limiting what changes are captured using a WHERE clause on the cloning command.
E) Create a Stream on the 'TRANSACTIONS' table and use a masking policy on the stream's output to redact the unnecessary columns.

3. You are tasked with sharing a subset of a customer table (CUSTOMER DATA') residing in your organization's Snowflake account with a partner organization. You need to mask personally identifiable information (PII) while providing near real-time updates. You decide to use a secure view. Which of the following SQL statements is the MOST efficient and secure way to accomplish this, assuming the partner only needs 'customer id', 'masked_email', 'city', and 'state'? The email should be masked using SHA256.

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

4. You have a Snowflake table 'CUSTOMER DATA with a column 'EMAIL' containing customer email addresses. You need to classify this column as 'PII' using a tag named 'SENSITIVITY' and value 'CONFIDENTIAL'. Also, you want all queries accessing this 'EMAIL' column to be logged, with specific details about who accessed it and when. You already have appropriate roles and privileges to perform the required operations. Which of the following SQL statements, when executed in sequence, will achieve this goal, assuming appropriate logging mechanisms are already configured to read from the Snowflake ACCESS HISTORY view?

A)

B)

C)

D)

E)

5. You have a base table 'ORDERS' with columns 'ORDER ID, 'CUSTOMER D', 'ORDER DATE, and 'ORDER AMOUNT'. You need to create a view that aggregates the total order amount per customer per month. However, for data governance purposes, you need to ensure that the view only shows data for the last 3 months. What is the MOST efficient and secure way to create this view in Snowflake?

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

Solutions: