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Last Updated: Aug 29, 2026
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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Transformation and Processing | 20-25% | - Transform and enrich data using SQL, JavaScript, Python, and Snowpark - Manage data quality, validation, and deduplication - Implement ELT/ETL workflows using Streams, Tasks, and Dynamic Tables - Process semi-structured data: JSON, Avro, Parquet, ORC |
| Topic 2: Data Governance, Security, and Compliance | 10-15% | - Apply data protection: encryption, masking, row-level security - Manage data lineage, cataloging, and compliance policies - Implement access control: RBAC, authentication, authorization - Enforce data quality and governance standards |
| Topic 3: Performance Optimization and Compute Management | 15-20% | - Manage virtual warehouses: sizing, scaling, multi-cluster, cost control - Monitor and tune workloads and resource utilization - Optimize query performance: clustering, partitioning, materialized views - Use search optimization and query acceleration services |
| Topic 4: Data Sharing and Collaboration | 5-10% | - Implement secure data sharing and data exchanges - Work with Snowflake Data Marketplace and external data providers - Design multi-tenant and cross-account data architectures |
| Topic 5: Data Ingestion and Sourcing | 20-25% | - Use Snowflake ingestion methods: Snowpipe, COPY INTO, External Functions - Design and implement continuous and batch ingestion pipelines - Ingest data from various sources: data lakes, APIs, on-premises systems, cloud storage - Handle different data formats: structured, semi-structured, unstructured |
| Topic 6: Data Pipeline Architecture and Design | 15-20% | - Integrate with external tools and platforms: orchestration, BI, ML - Build end-to-end near real-time streaming solutions - Apply design patterns for data engineering workloads - Design scalable, reliable, and maintainable data pipelines |
Question 1
You are working with a Snowflake table 'customer_data' which contains customer information stored in a VARIANT column named raw_info'. The 'raw_info' JSON structure includes nested addresses, and preferences. Your task is to extract the city from the first address in the 'addresses' array, and the customer's preferred communication method from the 'preferences' object. Some customers might not have addresses or preferences defined. Select the two SQL snippets that correctly and efficiently extract this data, handling missing fields gracefully and providing appropriate type casting. Address array is in the format 'addresses: [ { 'city': '...', 'state': ' '},
A. Option D
B. Option B
C. Option E
D. Option C
E. Option A
Question 2
A data provider wants to create a Listing in the Snowflake Marketplace. They want to ensure that consumers can only access the data in a secure and controlled manner. The provider needs to restrict data access based on specific roles within the consumer's Snowflake account and track data usage. Which of the following steps are NECESSARY to achieve these requirements?
A. Create a Reader Account and share the data through that account, managing access directly.
B. Implement a secure view with a 'WHERE clause that filters data based on the consumer's context and share the view in the Listing.
C. Implement row-level security policies on the shared tables and views to filter data based on consumer roles. Share the tables and views in the Listing. Monitor usage through Snowflake's account usage views.
D. Grant direct access to the underlying tables and views to the consumer's roles.
Question 3
You are planning to monetize a dataset on the Snowflake Marketplace. You want to provide potential customers with sample data to evaluate before they purchase a full subscription. Which of the following strategies are valid and recommended for offering a free sample of your data within the Snowflake Marketplace? (Select all that apply)
A. Create a separate share containing a subset (e.g., a smaller number of rows or columns) of the full dataset and offer this share as a free trial listing on the Marketplace.
B. Offer a 'free trial' subscription on the primary listing that automatically expires after a set period (e.g., 7 days), allowing customers to access the full dataset during the trial period. You will need to write custom code to manage trial expiration and data access restrictions based on the trial status.
C. Provide the consumer with the script to create a database link to your data, allowing them read-only access to a pre-defined sample table, and then revoke the access after a set period.
D. Create a view that filters the dataset based on a sampling algorithm (e.g., 'SAMPLE ROW' clause) and share the view through the Marketplace.
E. Upload a sample CSV file to a publicly accessible S3 bucket and provide the link in the Marketplace listing description. Consumers can download and load this data into their own Snowflake account for evaluation.
Question 4
You are the provider of a data product on the Snowflake Marketplace. You need to grant a trial access to a potential consumer You want to provide limited access for 7 days to specific tables in your database. Which of the following steps are REQUIRED to accomplish this?
(Select all that apply)
A. Monitor the consumer's query history to ensure they are only accessing the allowed tables.
B. Create a new share specifically for the trial consumer, granting USAGE privilege on the database and SELECT privilege on the specific tables.
C. Contact Snowflake support to enable trial access for the consumer's account.
D. Create a new role, grant USAGE privilege on the database and SELECT privilege on the specific tables to this role, and then grant this role to the trial consumer.
E. Grant OWNERSHIP on the specific tables to the consumer's account temporarily.
Question 5
You are designing a system to monitor data access patterns in Snowflake. You want to capture detailed information about all queries executed, including the user, query text, execution time, and any potential data access violations based on security policies. Which of the following approaches, used in combination, would provide the MOST comprehensive and scalable solution for this monitoring requirement? (Select TWO)
A. Enable the 'QUERY_HISTORY view in the 'ACCOUNT_USAGE' schema and periodically query it using a scheduled task.
B. Configure the 'SNOWFLAKE database's audit logs and stream them to an external security information and event management (SIEM) system.
C. Enable query tagging and insert custom tags into each SQL statement indicating sensitive data access. Then, query 'QUERY HISTORY filtering on these tags.
D. Implement Snowflake's Event Tables and configure them to capture security-related events, such as data access policy violations.
E. Create a stored procedure to intercept all SQL commands before execution, log them, and then execute them using 'EXECUTE IMMEDIAT
Solutions:
| Question 1 Answer: A,C | Question 2 Answer: C | Question 3 Answer: A,D | Question 4 Answer: B | Question 5 Answer: B,D |
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