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Snowflake DEA-C02 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Data Architecture and Processing | 20% | - Data Storage Architecture
|
| Performance Optimization | 15% | - Warehouse Performance
|
| Security and Governance | 15% | - Governance and Compliance
|
| Data Transformation with Snowflake | 30% | - Snowflake Scripting
|
| Data Ingestion and Consumption | 20% | - Bulk Loading and Unloading
|
Snowflake SnowPro Advanced: Data Engineer (DEA-C02) Sample Questions:
1. You have a table named 'TRANSACTIONS with the following definition: CREATE TABLE TRANSACTIONS ( TRANSACTION ID NUMBER, TRANSACTION DATE DATE, CUSTOMER_ID NUMBER, AMOUNT PRODUCT_CATEGORY VARCHAR(50) Users frequently query this table using filters on both 'TRANSACTION_DATE and 'PRODUCT CATEGORY. You want to optimize query performance. What is the MOST effective approach?
A) Partition the table by 'TRANSACTION DATE
B) Cluster the table on ' TRANSACTION_DATE and then create a materialized view filtered by PRODUCT_CATEGORY&.
C) Create separate indexes on 'TRANSACTION DATE' and 'PRODUCT CATEGORY.
D) Cluster the table using a composite key of '(TRANSACTION_DATE, PRODUCT CATEGORY)'.
E) Create a materialized view joining 'TRANSACTIONS' with a dimension table containing product category information.
2. You are tasked with implementing row-level security (RLS) on a 'SALES' table to restrict access based on the 'REGION' column. Users with the 'NORTH REGION ROLE should only see data where 'REGION = 'NORTH". You've created a row access policy named north_region_policy'. After applying the policy to the 'SALES table, users with the 'NORTH REGION ROLE are still seeing all rows.
Which of the following is the MOST likely reason for this and how can it be corrected?
A) The policy function within is not using the correct context function to determine the user's role. It should use 'CURRENT ROLE()' instead of 'CURRENT_USER()'
B) The policy needs to be explicitly refreshed. Execute 'REFRESH ROW ACCESS POLICY north_region_policy ON SALES;'
C) The user has not logged out and back in since the role was granted to them. Force the user to re-authenticate.
D) The is not enabled. Execute 'ALTER ROW ACCESS POLICY ON SALES SET ENABLED = TRUE;'
E) The ' does not have the USAGE privilege on the database and schema containing the 'SALES' table. Grant the USAGE privilege to the role.
3. You are using Snowpark to perform a complex join operation between two large tables: 'ORDERS (1 OOGB) and 'CUSTOMER (50GB). The join is performed on 'ORDERS.CUSTOMER ID = CUSTOMER.ID. The query is running slower than expected. You have already confirmed that the warehouse size is adequate. Which of the following strategies, applied in combination , would most likely improve the join performance within a Snowpark context?
A) Ensure both tables are clustered on the join keys CORDERS.CUSTOMER_ID' and 'CUSTOMER.ID').
B) Increase the 'AUTO RESIZE' setting on the warehouse to automatically scale up the warehouse size when the load increases.
C) Analyze the query profile in Snowflake's web UI to identify the specific bottleneck (e.g., excessive data spilling, high CPU utilization) and address it directly.
D) Use 'session.add_import to add external JAR dependencies. This would enable use of external libraries and improve performance.
E) Use Snowpark's 'hint function to force a broadcast join, assuming the 'CUSTOMER table can fit into memory on the worker nodes.
4. 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 A
B) Option C
C) Option D
D) Option E
E) Option B
5. Consider a scenario where you have a Snowflake table named 'CUSTOMER DATA' containing customer IDs (INTEGER) and encrypted credit card numbers (VARCHAR). You need to create a secure JavaScript UDF to decrypt these credit card numbers using a custom encryption key stored securely within Snowflake's internal stage, and then mask all but the last four digits of the decrypted number for data protection. Which of the following actions are necessary to ensure both functionality and security while adhering to Snowflake's best practices for UDF development and security?
A) Store the encryption key directly within the JavaScript UDF code as a string variable.
B) Use Snowflake's Secure Vault (Secret) feature to store the encryption key and retrieve it securely within the UDF.
C) Encrypt the key using a weaker encryption algorithm before storing it in an internal stage to balance security and performance.
D) Store the encryption key in a separate file on an internal stage accessible only by the UDF's service account and load the key from the file within the UDF at runtime.
E) Pass the encryption key as an argument to the UDF each time it is called.
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: E | Question # 3 Answer: A,C | Question # 4 Answer: D | Question # 5 Answer: B,D |
