Oracle Fusion Analytics Warehouse (FAW) extracts data from Oracle Cloud Applications via integration pipelines and surfaces that data in an Autonomous Data Warehouse. The data is structured into facts and dimensions which are modelled into structures called subject areas which are easy to visualise and explore using Oracle Analytics Cloud (OAC). A lot of pre-built content is provided, such as KPIs and Workbooks, to help to analyse the data from Cloud Applications. This platform can also be extended in a number of ways to explore data that is not directly sourced from Oracle Applications and so can allow FAW to act as a lens across data from across the enterprise.
One example we look at here is an extension to the semantic model to surface data that has not been populated by the pipeline from Oracle Cloud Applications, and this takes the form of analysing Co2 emissions from car journeys from staff in different departments.
One outline method for doing this is by :
- Creating a new custom schema (e.g. xxcustom_dw) in the provided Oracle Autonomous Data Warehouse. We can do this using SQL in Actions. We will need to allocate space on the DATA tablespace so that we can create objects.
- Creating new custom tables in the custom schema to hold the data we wish to model and explore.
- Populate the new tables with data and grant to the OAX$OAC user.
- The Oracle semantic model is immutable and managed by Oracle. New versions of FAW have a revised model which is under Oracle’s control. We can however extend it by creating branches to the Oracle delivered model.
- Create a new Subject Area for our Co2 analysis data.
- Create new dimensions and facts from the new custom tables we created.
- Create a model by using the modelling wizards to join the dimensions to the facts and create other structures (e.g. hierarchies).
- Complete the Subject Area by tidying up naming and column visibility.
- Consider any security requirements.
- Publish the new subject area so that it is available for use.
We can then use the new subject area and develop visualisations that have the same aesthetic as the Oracle supplied content so that visualisations and data analysis are carried out using a consistent interface
The short video below shows an example of using a slider to examine the Co2 data for three different dapartments using a selection of visualisation types available in the January 2023 version of OAC provided by FAW.