About Augmenting Your Data
Enhance the data used in your analytics with additional data, various calculations, and combinations to enable comprehensive analytics and multi-faceted visualizations. By augmenting the data, you can reduce or even eliminate the manual intervention in developing meaningful insight of the business data.
Add data to your reports from various data stores (Business Intelligence view objects) of the Oracle Applications Cloud data sources. You can augment your reports with datasets created by extending an existing entity or group of facts, by adding a new dimension in the target instance, and by adding a new fact in the target instance.
Select the columns from various data stores, create an augmentation dataset, and use that dataset to create data pipelines for functional areas. This enables you to seamlessly extract and load data from additional Oracle Applications Cloud data stores and make it readily available in tables populated in the autonomous data warehouse. You can then use the data for visualization and analysis. To find the data stores that are available for extraction using augmentation, see the Data Stores section in Reference for Oracle Fusion SCM Analytics, Reference for Oracle Fusion HCM Analytics, and Reference for Oracle Fusion ERP Analytics. Although there is no technical limit, you can create a maximum of hundred data augmentations for a single tenant to ensure optimal performance of all data pipelines. Contact Oracle Support if you have further questions.
- Product sales – Add similar product information from different data sources to create a report that compares similar products in a specific region.
- Average of expense invoices – Add various expense invoices to create an average of periodic expenses.
Augment Your Data
You can supplement the data in your reports by using datasets that you create with specific columns from various data stores (Business Intelligence view objects) of the Oracle Applications Cloud data sources.
You can use the system provided or customer provided source tables. The system provided tables are pre-validated by Oracle Fusion Analytics Warehouse. The customer provided tables are other source tables that are available for extraction but aren’t validated by Oracle Fusion Analytics Warehouse. As a user with the functional administrator or system administrator application role, you can allow usage of a particular table that isn’t pre-validated by Oracle Fusion Analytics Warehouse. However, be aware that Oracle can't assure the performance of processing such customs tables. Adding such custom tables can delay the daily data refresh.
- Activation in Progress - You can’t edit, delete, or schedule a data augmentation pipeline job while activation is in progress.
- Activation Completed - You can edit the data augmentation to add or delete VO attributes and save the changes. You can’t modify the schedule in this status.
- Activation Scheduled - You can edit the data augmentation to add VO attributes, save the changes while retaining the existing schedule, reschedule the execution date and time, or execute the plan immediately.
Note:
Later if you delete a data augmentation, then you must wait for the daily incremental run to complete to see the change in the reports, cards, and decks.Create Dimension Augmentation Type
You can augment your reports with datasets created by adding a new dimension in the target instance.
- In step 1 of the Data Augmentation wizard, select Create Dimension to add a new dimension in the target instance.
- Select Supplemental Data (Regular) as the source dataset type.
- Select a product pillar; for example, Enterprise Resource Planning.
- In Source Table Type, specify the source table type using either of the options:
- Select System Provided and then in Source Table, select a table to which you want to add the new dimension.
- Select Customer Provided and then in Source Table, enter the name of the table to which you want to add the new dimension.
- Click Next.
- In step 2 of the wizard, select the check box for the attributes from the source table that you want in your new dimension, and then click Next.
- In step 3 of the wizard, click Action icon for each of the selected attributes to specify the Type and Treat as settings.
- Click Next.
- In step 6 of the wizard, provide the following details and click Finish to save and schedule your data augmentation pipeline job:
- Name your augmentation pipeline job; for example, Customer Class Code.
- Enter a suffix for the target table name using underscore in place of spaces between words and don’t use special characters; for example, Customer_Class_D. The augmentation process automatically creates the target table name.
- Provide a description.
- Select the functional area and one or multiple subject areas in which you want to include this augmentation pipeline job.
- Specify the options to save the data augmentation pipeline job without executing it, or schedule the execution date and time, or execute it immediately.
Create Fact Augmentation Type
You can augment your reports with datasets created by adding a new fact in the target instance.
Extend an Entity
You can augment your reports with datasets created by extending an existing entity or group of facts.
- In step 1 of the Data Augmentation wizard, select Extend Entity.
- Select Descriptive Flex Field (New) as the source dataset type.
- Select a product pillar; for example, Enterprise Resource Planning.
- In Source Table Type, specify the source table type using either of the options:
- Select System Provided and then in Source Table, select a table to which you want to add the new dimension.
- Select Customer Provided and then in Source Table, enter the name of the table to which you want to add the new dimension.
- Select a source table from the list of view objects that support descriptive flex fields and then click Next.
- In step 2 of the wizard, select the check box for the attributes from the source table that you want in your target table, and then click Next.
- In step 3 of the wizard, click Action icon for each of the selected attributes to specify the Type and Treat as settings, and then click Next.
- In step 4 of the wizard, select the entity or group of fact tables to extend and its primary keys, and then click Next. For example, if you select ARTransaction as the entity to extend, then this process joins the ready-to-use InvoiceID descriptive flex field using the “s_k_5000” primary join key with all the fact tables in the ARTransaction entity.
- In step 5 of the wizard, choose the primary keys for the attributes that you had specified to be treated as dimensions.
- In step 6 of the wizard, provide the following details and click Finish to save and schedule your data augmentation pipeline job:
- Name your augmentation pipeline job; for example, AP Invoice Header.
- Enter a suffix for the target table name using underscore in place of spaces between words and don’t use special characters; for example, AP_Invoice_Header_DFF. The augmentation process automatically creates the target table name.
- Provide a description.
- Select the functional area and one or multiple subject areas in which you want to include this augmentation pipeline job.
- Specify the options to save the data augmentation pipeline job without executing it, or schedule the execution date and time, or execute it immediately.