Question 1
Choose 1
A Data 360 Consultant is explaining the benefits of zero-copy data federation to a stakeholder. Which statement best describes how data federation differs from traditional data ingestion in Data 360?
Correct answer:
C. Data federation allows Data 360 to read data directly from an external provider without moving or
copying the data.
Explanation:
Data federation (also called zero-copy) allows Data 360 to access and query data directly from external data sources without copying or moving it into Data 360 storage. Instead of ingesting data, Data 360 creates an external Data Lake Object (DLO) that acts as a reference pointing to the data physically stored in the external system . This eliminates the need for duplication and enables real-time access to external data.
Correct Option:
C. Data federation allows Data 360 to read data directly from an external provider without moving or copying the data.
This accurately describes the core benefit of data federation. Data stays in its original location (such as Snowflake, Databricks, or BigQuery), and Data 360 queries it in place using Apache Iceberg or other supported connectors. This approach reduces storage costs, eliminates data duplication, and ensures data freshness since queries retrieve the most current information directly from the source .
Incorrect Option:
A. Data federation requires data to be converted into CSV format before it can be accessed.
Data federation does not require CSV conversion. It supports open table formats like Apache Iceberg and connects directly to external data platforms through supported connectors. The data remains in its native format and is queried in place .
B. Data federation copies all data into Data 360 storage every 15 minutes.
This describes caching or accelerated query behavior, not federation itself. Data federation by definition does not copy data into Data 360. While caching can be optionally enabled to improve performance for frequently accessed data, it is not a requirement of federation .
D. Data federation only supports data coming from other Salesforce orgs.
This is incorrect. Data federation in Data 360 supports external platforms including Snowflake, Databricks, Google BigQuery, Amazon Redshift, AWS Glue Data Catalog, and other Iceberg-compatible data sources—not just Salesforce orgs .
Reference:
Salesforce Help: Data Federation, Ingestion, and Modeling; Salesforce Help: Caching or Acceleration in Data Federation; Salesforce Blog: Unlock Trapped Data in Your Data Lakes.
Data federation (also called zero-copy) allows Data 360 to access and query data directly from external data sources without copying or moving it into Data 360 storage. Instead of ingesting data, Data 360 creates an external Data Lake Object (DLO) that acts as a reference pointing to the data physically stored in the external system . This eliminates the need for duplication and enables real-time access to external data.
Correct Option:
C. Data federation allows Data 360 to read data directly from an external provider without moving or copying the data.
This accurately describes the core benefit of data federation. Data stays in its original location (such as Snowflake, Databricks, or BigQuery), and Data 360 queries it in place using Apache Iceberg or other supported connectors. This approach reduces storage costs, eliminates data duplication, and ensures data freshness since queries retrieve the most current information directly from the source .
Incorrect Option:
A. Data federation requires data to be converted into CSV format before it can be accessed.
Data federation does not require CSV conversion. It supports open table formats like Apache Iceberg and connects directly to external data platforms through supported connectors. The data remains in its native format and is queried in place .
B. Data federation copies all data into Data 360 storage every 15 minutes.
This describes caching or accelerated query behavior, not federation itself. Data federation by definition does not copy data into Data 360. While caching can be optionally enabled to improve performance for frequently accessed data, it is not a requirement of federation .
D. Data federation only supports data coming from other Salesforce orgs.
This is incorrect. Data federation in Data 360 supports external platforms including Snowflake, Databricks, Google BigQuery, Amazon Redshift, AWS Glue Data Catalog, and other Iceberg-compatible data sources—not just Salesforce orgs .
Reference:
Salesforce Help: Data Federation, Ingestion, and Modeling; Salesforce Help: Caching or Acceleration in Data Federation; Salesforce Blog: Unlock Trapped Data in Your Data Lakes.