SnowPro-Core Exam Study Guide Free Practice Test LAST UPDATED DATE Jul 01, 2024
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Snowflake SnowPro-Core certification is a highly sought-after certification for professionals in the field of data warehousing and analytics. SnowPro Core Certification Exam certification is designed to validate the skills and knowledge required to design, build, and manage modern data warehousing solutions using the Snowflake platform. The SnowPro-Core exam is the foundation-level certification exam that covers the basic concepts and skills required to work with Snowflake.
Snowflake SnowPro-Core certification exam is designed for individuals who have a good understanding of data warehousing concepts and have experience working with Snowflake's cloud data platform. SnowPro Core Certification Exam certification exam consists of multiple-choice questions and covers topics such as Snowflake architecture, data loading and unloading, data modeling, performance optimization, and security. SnowPro-Core exam is conducted online and can be taken from anywhere in the world.
NEW QUESTION # 294
True or False: Pipes can be suspended and resumed.
- A. True
- B. False
Answer: B
NEW QUESTION # 295
When unloading to a stage, which of the following is a recommended practice or approach?
- A. Avoid the use of the CAST function
- B. Define an individual file format
- C. Use OBJECT_CONSTRUCT ( * ) when using Parquet
- D. Set SINGLE: = true for larger files
Answer: A
NEW QUESTION # 296
Which of the following features are available with the Snowflake Enterprise edition? (Choose two.)
- A. Customer managed keys (Tri-secret secure)
- B. Native support for geospatial data
- C. Automated index management
- D. Database replication and failover
- E. Extended time travel
Answer: D,E
Explanation:
The Snowflake Enterprise edition includes database replication and failover for business continuity and disaster recovery, as well as extended time travel capabilities for longer data retention periods1.
NEW QUESTION # 297
A company needs to allow some users to see Personally Identifiable Information (PII) while limiting other users from seeing the full value of the PII.
Which Snowflake feature will support this?
- A. Data encryption
- B. Data masking policies
- C. Role based access control
- D. Row access policies
Answer: B
Explanation:
Data masking policies in Snowflake allow for the obfuscation of specific data within a field, enabling some users to see the full data while limiting others. This feature is particularly useful for handling PII, ensuring that sensitive information is only visible to authorized users1.
NEW QUESTION # 298
Which of the following describes a Snowflake stored procedure?
- A. They can be created to run with a caller's rights or an owner's rights.
- B. They can contain only a single SQL statement.
- C. They can only access tables from a single database.
- D. They can be created as secure and hide the underlying metadata from the user.
Answer: A
Explanation:
Snowflake stored procedures can be created to execute with the privileges of the role that owns the procedure (owner's rights) or with the privileges of the role that calls the procedure (caller's rights). This allows for flexibility in managing security and access control within Snowflake1.
NEW QUESTION # 299
What Snowflake role must be granted for a user to create and manage accounts?
- A. ACCOUNTADMIN
- B. ORGADMIN
- C. SECURITYADMIN
- D. SYSADMIN
Answer: A
Explanation:
The ACCOUNTADMIN role is required for a user to create and manage accounts in Snowflake. This role has the highest level of privileges and is responsible for managing all aspects of the Snowflake account, including the ability to create and manage other user accounts1.
https://docs.snowflake.com/en/user-guide/security-access-control-considerations.html
NEW QUESTION # 300
Which Snowflake technique can be used to improve the performance of a query?
- A. Clustering
- B. Indexing
- C. Fragmenting
- D. Using INDEX__HINTS
Answer: A
Explanation:
https://docs.snowflake.com/en/user-guide/tables-clustering-keys.html
NEW QUESTION # 301
How can a user get the MOST detailed information about individual table storage details in Snowflake?
- A. SHOW EXTERNAL TABLES command
- B. SHOW TABLES command
- C. TABLES view
- D. TABLE STORAGE METRICS view
Answer: D
Explanation:
To get the most detailed information about individual table storage details in Snowflake, the TABLE STORAGE METRICS view should be used. This Information Schema view provides granular storage metrics for tables within Snowflake, including data related to the size of the table, the amount of data stored, and storage usage over time. It's an essential tool for administrators and users looking to monitor and optimize storage consumption and costs.
References:
* Snowflake Documentation: Information Schema - TABLE STORAGE METRICS View
NEW QUESTION # 302
Which Snowflake feature records changes mace to a table so actions can be taken using that change data capture?
- A. Task
- B. Stream
- C. Pipe
- D. Materialized View
Answer: B
Explanation:
Snowflake's Streams feature is specifically designed for change data capture (CDC). A stream records insert, update, and delete operations performed on a table, and allows users to query these changes. This enables actions to be taken on the changed data, facilitating processes like incremental data loads and real-time analytics. Streams provide a powerful mechanism for applications to respond to data changes in Snowflake tables efficiently.References: Snowflake Documentation on Streams
NEW QUESTION # 303
True or False: Snowflake's data warehouse was built from the ground up for the cloud in lieu of using an existing database or a platform, like Hadoop, as a base.
- A. True
- B. False
Answer: B
Explanation:
Reference: https://docs.snowflake.com/en/user-guide/intro-key-concepts.html
NEW QUESTION # 304
What operations can be performed while loading a simple CSV file into a Snowflake table using the COPY INTO command? (Select TWO).
- A. Converting the datatypes
- B. Performing aggregate calculations
- C. Grouping by operations
- D. Selecting the first few rows
- E. Reordering the columns
Answer: A,E
Explanation:
When loading a simple CSV file into a Snowflake table using the COPY INTO command, you can perform various transformations and adjustments on the data as part of the loading process. Specifically, you can:
* B. Reorder the columns: Specify the order of columns in the COPY INTO command to match the structure of the target table if it differs from the order of columns in the source CSV file.
* D. Convert the datatypes: Explicitly convert the datatypes of the data being loaded to match the datatypes of the columns in the target table. This can be necessary when the source data's format does not match the target table's expected datatype.
References:
* Snowflake Documentation: Using the COPY INTO Command for Data Loading
NEW QUESTION # 305
Which types of subqueries does Snowflake support? (Select TWO).
- A. Uncorrelated scalar subqueries in any place that a value expression can be used
- B. EXISTS, ANY /ALL, and IN subqueries in WHERE clauses: these subqueries can be correlated or uncorrelated
- C. Uncorrelated scalar subqueries in WHERE clauses
- D. EXISTS, ANY / ALL, and IN subqueries in WHERE clauses: these subqueries can be uncorrelated only
- E. EXISTS, ANY / ALL, and IN subqueries in where clauses: these subqueries can be correlated only
Answer: A,B
Explanation:
Snowflake supports a variety of subquery types, including both correlated and uncorrelated subqueries. The correct answers are B and E, which highlight Snowflake's flexibility in handling subqueries within SQL queries.
* Uncorrelated Scalar Subqueries: These are subqueries that can execute independently of the outer query. They return a single value and can be used anywhere a value expression is allowed, offering great flexibility in SQL queries.
* EXISTS, ANY/ALL, and IN Subqueries: These subqueries are used in WHERE clauses to filter the results of the main query based on the presence or absence of matching rows in a subquery. Snowflake supports both correlated and uncorrelated versions of these subqueries, providing powerful tools for complex data analysis scenarios.
* Examples and Usage:
* Uncorrelated Scalar Subquery:
SELECT * FROM employees WHERE salary > (SELECT AVG(salary) FROM employees);
* Correlated EXISTS Subquery:
SELECT * FROM orders o WHERE EXISTS (SELECT 1 FROM customer c WHERE c.id = o.customer_id AND c.region = 'North America'); Reference: For comprehensive details on the types of subqueries supported by Snowflake and examples of their usage, consult the Snowflake documentation on subqueries:
https://docs.snowflake.com/en/sql-reference/constructs/subqueries.html
NEW QUESTION # 306
The PUT command: (Choose two.)
- A. Automatically creates a File Format object
- B. Automatically encrypts files
- C. Automatically uses the last Stage created
- D. Automatically compresses files using Gzip
Answer: B,D
Explanation:
Reference: https://docs.snowflake.com/en/sql-reference/sql/put.html
NEW QUESTION # 307
What is the purpose of a Query Profile?
- A. To profile how many times a particular query was executed and analyze its u^age statistics over time.
- B. To profile which queries are running in each warehouse and identify proper warehouse utilization and sizing for better performance and cost balancing.
- C. To profile the user and/or executing role of a query and all privileges and policies applied on the objects within the query.
- D. To profile a particular query to understand the mechanics of the query, its behavior, and performance.
Answer: D
Explanation:
The purpose of a Query Profile is to provide a detailed analysis of a particular query's execution plan, including the mechanics, behavior, and performance. It helps in identifying potential performance bottlenecks and areas for optimization
NEW QUESTION # 308
Which of the following Snowflake capabilities are available in all Snowflake editions? (Select TWO)
- A. Up to 90 days of data recovery through Time Travel
- B. Customer-managed encryption keys through Tri-Secret Secure
- C. Automatic encryption of all data
- D. Object-level access control
- E. Column-level security to apply data masking policies to tables and views
Answer: C,D
Explanation:
In all Snowflake editions, two key capabilities are universally available:
* B. Automatic encryption of all data: Snowflake automatically encrypts all data stored in its platform, ensuring security and compliance with various regulations. This encryption is transparent to users and does not require any configuration or management.
* D. Object-level access control: Snowflake provides granular access control mechanisms that allow administrators to define permissions at the object level, including databases, schemas, tables, and views.
This ensures that only authorized users can access specific data objects.
These features are part of Snowflake's commitment to security and governance, and they are included in every edition of the Snowflake Data Cloud.
References:
* Snowflake Documentation on Security Features
* SnowPro Core Certification Exam Study Guide
NEW QUESTION # 309
If queries start to queue in a multi-cluster virtual warehouse, an additional compute cluster starts immediately under what setting?
- A. Standard scaling policy
- B. Auto-scale mode
- C. Maximized mode
- D. Economy scaling policy
Answer: A
NEW QUESTION # 310
Snowflake provides a mechanism for its customers to override its clustering algorithms. This method is:
- A. Micro-partitions
- B. Clustered partitions
- C. Key partitions
- D. Clustering keys
Answer: D
Explanation:
Reference: https://community.snowflake.com/s/article/Snowflake-What-the-Cluster
NEW QUESTION # 311
Which interfaces can be used to create and/or manage Virtual Warehouses?
- A. SQL commands
- B. All of the above
- C. Data integration tools
- D. The Snowflake Web Interface (UI)
Answer: A
NEW QUESTION # 312
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