With Input from Brian Ramos, Senior Principal Product Manager, Fusion Warehouse Management – Development

Validation

Content validated on 05/08/2023 with

• ADW Version Oracle Database 19c Enterprise Edition Release – Production Version 19.11.0.0.0

• Oracle Cloud Application 23B (11.13.23.04.0)

• Fusion Analytics Warehouse Application Version  23.R2

• Oracle Transportation Management (OTM) Cloud 23C

 Background

Oracle Fusion Analytics provides analytics for Oracle Cloud applications, powered by Autonomous Data Warehouse and Oracle Analytics. More specifically:

• Fusion ERP Analytics provides accounting data sourced from ERP Cloud in a warehouse designed to support broad set of analytics use cases. 
• Fusion HCM Analytics provides comprehensive workforce, turnover data sourced from Fusion HCM Cloud.
• Fusion SCM Analytics give customers the ability to gain visibility into Supply Chain performance, correlate Supply Chain processes with business goals and detect, understand and predict Supply Chain issues.

Making the right business decisions is intrinsinclty tied to the system of records data accuracy of a company. In many specific use cases, Fusion Analytics data can be complemented with additional data from external source such as On Premise, Legacy applications, Non Fusion SaaS application, OCI source, Third party cloud applications, and so on…

To support these data enrichment and consilidation requirements, Fusion Analytics is introducing a new Connectors to leverage the Fusion Analytics Oracle data pipeline infrastructure to extract data (full and incremental) from these external sources following a defined schedule, potentially reducing custom data extraction code, infrastructure and platform costs.

This blog describes how to utilize Fusion Analytics (FAW) Data Augmentation feature to replicate transaction data from OTM Cloud into ADW to extend the Data Layer of FAW. 

These data sets can provide critical insight when merge with Fusion ERP data.

Suggested Prerequisite Reading Material:

* Data Augmentation with FAW 

* Data Replication with OAC 

* FAW Semantic Model Customization

Overall prerequisites

* Have access to an Fusion Analytics Instance (OAC, ADW) with Administrative privileges

* Have configured SQL level access to Fusion Analytics ADW, as described in Krithika and Gunaranjan blog post here.

 Architecture Overview

FAW Data Augmentation allows customers to leverage the FAW data pipeline to augment reports with datasets created :

1. By adding a new dimension in the target instance,
2. By adding a new fact in the target instance.

The diagram below details the architecture for the Connectors :

Figure 1: FAW Data Augmentation flow with OTM Connector

The high level configuration flow is as follow:

• OTM Configuration

  • Create Application in IDCS

  • Edit OAuth Configuration in IDCS

  • Create OTM User with Data Export API – REST Access Control granted

• FAW Configuration

  • Enable OTM feature

  • Create OTM Connection

  • Test Connection

  • Refresh metadata for OTM connection

  • Set Pipeline Settings

  • Create OTM data augmentations

• FAW Data Pipeline processes the data augmentation pipeline jobs, extract the data from OTM tables and load it into ADW, queryable via synonyms starting with DW_OTM_X_

• Augmented data can be then queried directly using OAC Data set or a SQL client like SQL developer, through the database synonym named after the table name give in the first step 

• Semantic model can be extended by using semantic model extension or External Application merge feature allow reporting on augmented data extracted in ADW. We will cover the basics here to be able to build a visualization against the extracted OTM Data. External Application merge will be documented a future blog.

BLS and Fusion Analytics Configuration

Let’s watch the video now

Figure 2: OTM and Fusion Analytics Connector configuration

 Creating OAC Artifacts to Gain Business Insight with OTM Data

Now that the Data Augmentation have completed,  we can create Data Sets and Workbooks

Figure 3: OTM Data Set

This concludes the activities in the blog.

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 Summary

This blog described how to utilize Fusion Analytics (FAW) Data Augmentation Connector to replicate transactions data from US Bureau of Labor Statistics into Autonomous Data Warehouse (ADW) to extend the Data Layer of FAW. This blog also detailed the steps to allow customers to answer business questions and gaining business insight with BLS and Fusion Analytics Data.

Bookmark this post to stay up-to-date on changes made to this blog as our products evolve.