Which statement best describes the purpose of Data Augmentation in Fusion Applications analytics?

Which statement best describes the purpose of Data Augmentation in Fusion Applications analytics?

• A. To move in additional content from Fusion Applications.
• B. To transform data into a different schema.
• C. To remove data noise.
• D. To replace the existing subject area.

Answer: (A)

Data augmentation in Fusion Applications analytics is about enriching the analytic dataset by bringing in additional content from Fusion Applications. This means expanding what’s available for analysis, adding more attributes and records to provide fuller context and better insights. The aim is to supplement the existing data with extra material to improve analytics outcomes, not to reshape the data schema, clean noise, or replace the current subject area. Transforming data into a different schema is a separate data modeling task; removing data noise is data cleansing; replacing the current subject area would discard valuable context. By moving in additional content, you enable more comprehensive analyses and stronger decision support.

Data augmentation in Fusion Applications analytics is about enriching the analytic dataset by bringing in additional content from Fusion Applications. This means expanding what’s available for analysis, adding more attributes and records to provide fuller context and better insights. The aim is to supplement the existing data with extra material to improve analytics outcomes, not to reshape the data schema, clean noise, or replace the current subject area. Transforming data into a different schema is a separate data modeling task; removing data noise is data cleansing; replacing the current subject area would discard valuable context. By moving in additional content, you enable more comprehensive analyses and stronger decision support.