Oracle Fusion BI Publisher Data Models to Fabric SQL: Steps to Plug-n-Play BI Connector's Fabric Pipeline Template

Modified on Mon, 10 Aug at 9:30 AM

COMMENT: Need help navigating the support articles? Go to Get Started

 

COMMENT: First Fabric case-specific article (Data Models to Fabric SQL). Steps 7-8 and the info cards are copied verbatim from 8000130392. Before publishing, insert screenshots at the [SCREENSHOT] markers. Eventual plan: add a path-chooser card near Step 6 in 8000130392 and trim 8000130392 to Steps 1-5.

 

Before you start

 

This path — covers pipelining BI Publisher Data Models to Fabric SQL. It continues from Step 4 of the Microsoft Fabric pipeline guide, gives the exact field mappings for Step 5, then the steps to schedule and run.

 

Steps 5 to 7 — Map, schedule, and run

Step 5 — Map the pipeline fields (Data Models to Fabric SQL)

Refer the screenshot of the Plug-n-play Pipeline template below for quick navigational reference.


BI Connector's Fabric Pipeline Template for Oracle Fusion


Tip — Haven't received the Plug-n-Play Pipeline Template like above from the BI Connector Team yet? Contact BI Connector


Complete the mappings row by row by referring to the table below.

For each row, start from the cell in the left. Complete the steps in that left-most cell, and move on to the steps on the cells in the right. After the steps in a row is completed fully, start from the left cell in the next row.


Finish the steps in all the rows.

COMMENT: [SCREENSHOT 1: Fabric pipeline canvas with the LOOP_THROUGH_MAPPINGS ForEach, the Activities Edit (pencil) box, and the sub-activities inside]

 

Pipeline activity (and sub-activities nav)Activity tabMappings
→ Click LOOP_THROUGH_MAPPINGS in the top pane
→ Click Edit in the Activities box
→ Double-click GET_ALL_DATA_FROM_FUSION
Click the Destination tab at the bottom paneMap the following in the bottom pane:
Connection — Map the Fabric SQL Connection
SQL Database — Map the database
→ Double-click GET_DELTA_DATA in the top pane Click the Destination tab at the bottom paneMap the following in the bottom pane:
Connection — Map the Fabric SQL Connection
SQL Database — Map the database
→ Double-click UPDATE_LOOKUP_STATUS_FULL_LOAD in the top pane Click the Settings tab at the bottom paneMap the following in the bottom pane:
Connection — Map the Fabric SQL Connection
SQL Database — Map the database
Stored Procedure Name — Click Refresh next to the dropdown and select the stored procedure you created before (default [dbo].[UPDATE_LOOKUP_STATUS])
→ Double-click UPDATE_LOOKUP_STATUS_INCR_LOAD in the top pane Click the Settings tab at the bottom pane Map the following in the bottom pane:
Connection — Map the Fabric SQL Connection
SQL Database — Map the database
Stored Procedure Name — Click Refresh next to the dropdown and select the stored procedure you created before (default [dbo].[UPDATE_LOOKUP_STATUS])
COMMENT: [SCREENSHOT 2: A sub-activity open with its Destination tab (Copy activities) and Settings tab (Stored Procedure activities) at the bottom]

 

 

Step 6 — Schedule automated runs

Click the Schedule option on the top ribbon and set up the refresh schedule for automated pipeline runs.

 

Step 7 — Run the pipeline

Trigger the first pipeline run by clicking the Run option on the top ribbon. Enter the Lookup table name and Destination schema name on the prompted parameter values.


After the run completes, you can verify if the pipeline executed successfully by checking the tables loaded on to the destination schema. The next run would automatically kick-in based on the schedule you set in step 6.

How the pipeline works: The first run performs a full load of all tables. Subsequent runs perform incremental refresh based on the configuration in each row of the Lookup table. The pipeline also automatically creates the destination tables and their column definitions if they do not already exist in the schema. It handles idempotency (updating existing rows based on the Primary Key defined in the Lookup table), identifies and adds new rows, and includes built-in error handling and retry mechanisms.
Tip — Need to pipeline additional tables later? Add the new rows to the Lookup table in BI Connector and update the Lookup table in your destination platform. The pipeline will automatically pick up and process the new rows in its next scheduled run.