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| Section | Objectives |
|---|---|
| Topic 1: Data Protection, Security, and Performance | - Time Travel and Fail-safe concepts - Role-based access control (RBAC) - Query performance optimization basics |
| Topic 2: Data Transformations and Querying | - Semi-structured data handling (VARIANT, JSON, Parquet) - SQL querying in Snowflake |
| Topic 3: Snowflake Architecture and Overview | - Snowflake architecture concepts (cloud data platform, separation of storage and compute) - Virtual warehouses and resource scaling concepts |
| Topic 4: Data Loading and Unloading | - Data unloading and external stages - Bulk loading using stages and COPY INTO |
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NEW QUESTION # 47
Who can access the data published in a Data Exchange?
Answer: B
Explanation:
Snowflake's Data Exchange allows data providers to publish data that is accessible only to users they explicitly invite. This mechanism ensures that only approved users or Snowflake accounts have access, adding a layer of security and control. Invited users can query the shared data directly within their Snowflake account without requiring data copies, reducing redundancy and enhancing data accessibility within controlled boundaries. This selective sharing feature is part of Snowflake's secure data-sharing capabilities.
NEW QUESTION # 48
What is the recommended file sizing for data loading using Snowpipe?
Answer: A
Explanation:
https://www.phdata.io/blog/how-to-optimize-snowpipe-data-load/#:~:text=Snowpipe%20is%20typically%20used%20to,data%20within%20one%2Dminute%20intervals.
NEW QUESTION # 49
Which minimum Snowflake edition allows for a dedicated metadata store?
Answer: D
Explanation:
The Enterprise edition of Snowflake allows for a dedicated metadata store, providing additional features designed for large-scale enterprises
NEW QUESTION # 50
How can a data provider ensure that a data consumer is going to have access to the required objects?
Answer: D
Explanation:
To ensure a data consumer has access to the required objects, a data provider can enable the data sharing feature and validate that the consumer can access the views or tables shared with them. Reference: Based on general data sharing practices in cloud services as of 2021.
NEW QUESTION # 51
What is the benefit of using the STRIP_OUTER_ARRAY parameter with the COPY INTO <table> command when loading data from a JSON file into a table?
Answer: B
Explanation:
The STRIP_OUTER_ARRAY parameter in the COPY INTO <table> command is used when loading data from a JSON file into a table. This parameter removes the outer array structure from the JSON data and loads separate rows of data into the table.
* Understanding the STRIP_OUTER_ARRAY Parameter:
* JSON files often contain data in an array format where multiple records are nested within a single outer array.
* The STRIP_OUTER_ARRAY parameter helps in simplifying the loading process by removing this outer array, allowing each element within the array to be loaded as a separate row in the target table.
* How It Works:
* When the STRIP_OUTER_ARRAY parameter is set to TRUE, Snowflake treats each item within the outer array as an individual record.
* This eliminates the need for additional parsing or transformation steps that would otherwise be required to handle nested arrays.
* Example Usage:
FROM @my_stage/file.json
FILE_FORMAT = (TYPE = 'JSON' STRIP_OUTER_ARRAY = TRUE);
* In this example, the JSON file containing an array of objects is loaded into the tablemy_table.
* Each object within the array is loaded as a separate row, without the outer array structure.
* Benefits:
* Simplifies data loading: By removing the outer array, the data is directly loaded into the table without additional manipulation.
* Enhances performance: Streamlines the loading process, reducing the complexity and potential errors in handling nested JSON structures.
:
Snowflake Documentation: COPY INTO <table>
Snowflake Documentation: JSON File Format Options
NEW QUESTION # 52
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