ADW Version Oracle Database 19c Enterprise Edition Release – Production Version 19.11.0.0.0
Oracle Cloud Application 22C (11.13.22.07.0)
Fusion Analytics Warehouse Application Version 23.R1
Shopify Trial / Basic Plan
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 Shopify Stores into ADW to extend the Data Layer of FAW.
* Have access to an Fusion Analytics Instance (OAC, ADW) with Administrative privileges
* Have access to a Shopify Account with a trial or basic plan
* 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 :
By adding a new dimension in the target instance,
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 Shopify Connectors
The high level configuration flow is as follow:
Shopify Configuration
Pre requisites : have created a Shopify Account (trial)
Create a custom Developer App in Shopify Admin
Configure custom App Admin API scopes (data elements that can be extracted)
Install custom App
Reveal and save Admin API Access Token
FAW Configuration
Enable Shopify feature
Create Shopify Connection
Test Connection
Refresh metadata for Shopify connection
Set Pipeline Settings
Create Shopify data augmentations
FAW Data Pipeline processes the data augmentation pipeline jobs, extract the data from Shopify tables and load it into ADW, queryable via synonyms starting with DW_SPFY_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 customizing an existing subject area or addition of a new subject area to allow reporting on augmented data extracted in ADW. This will require the creation of database objects (views and grants). We will cover the basics here to be able to build a visualization against the extracted Shopify Data.
Shopify and Fusion Analytics Configuration
Let’s watch the video now
Figure 2: Shopify and Fusion Analytics Connector configuration
Accessing an OAC Workbook to Gain Business Insight with Shopify Data
Now that the Data Augmentation have commpleted, we can create Data Sets and Workbooks
Figure 3: Shopify visualization
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 Shopify Cloud Applications into Autonomous Data Warehouse (ADW) to extend the Data Layer of FAW. This blog also detailed the steps to extend the semantic model to ultimate allow customers to answer business questions and gaining business insight with Shopify and Fusion Analytics Data.
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Authors
Matthieu Lombard
Consulting Solution Architect
The Oracle A-Team is a central, outbound, highly technical team of enterprise architects, solution specialists, and software engineers.
The Oracle A-Team works with external customers and Oracle partners around the globe to provide guidance on implementation best practices, architecture design reviews, troubleshooting, and how to use Oracle products to solve customer business challenges.
I focus on data integration, data warehousing, Big Data, cloud services, and analytics (BI) products. My role included acting as the subject-matter expert on Oracle Data Integration and Analytics products and cloud services such as Oracle Data Integrator (ODI), and Oracle Analytics Cloud (OAC, OA For Fusion Apps, OAX).