Extending Fusion Analytics - Part 2 of 4

January 10, 2023 | 4 minute read
Duncan Fitter
Director of Product Strategy, Oracle Analytics, Product Management
Kiriti Mukherjee
Senior Principal Product Manager, Oracle Analytics, Product Management
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Moving beyond Fusion data & delivering deeper insights with Fusion Analytics

We began our journey in our previous blog post: “Starting your Fusion Analytics Journey” which can be found here.

Next up… we will discuss the various ways to move to delivering deeper and richer insights by bringing in non-Fusion data and combining it with Fusion data.

Enrich our insights by combining in some other data quickly…

Within the front-end self-service capabilities of Oracle Analytics Cloud (OAC), a Business Analyst can easily pull in a flat file (such as Excel) and marry it to the Fusion data, Figure 7.

Scenario: Reviewing why people are leaving a company. The core data to this can be found in Fusion, however recruitment data may be in an Excel file. By combining those two sources, you might be able to identify which recruitment agency is tied to particular outcomes. For example, one agency might be recruiting all the top-performers, but they are the ones leaving. Based on this data and analysis, you could act by encouraging recruiters to set expectations more appropriately with candidates.

Figure 7
Figure 7

What happens if your data isn’t in a flat file?  The OAC component of Fusion Analytics has the capability to allow a live data connect to various data sources to be carried out, Figure 8.

Continuing with our previous example, if the recruitment data is not in an Excel file, the Business Analyst can simply connect to that live source and join their data to undertake their analysis as before.

Figure 8
Figure 8

IT provides governance, structure and regularity to data ingest

Figures 7 and 8 exemplify how the Business Analyst can quickly and easily bring in additional data for a one-off piece of analysis, or re-fresh that data on an ad hoc basis to undertake the analysis needed.

Following our previous example, in an organisation which employs hundreds of thousands of people, continuous recruitment is crucial, and they may wish to involve IT to bring in data regularly and a more robust way. Or employee onboarding data, time and labour or labour scheduling, perhaps coming from a source such as Kronos.

This more structured approach would enable data to be brought in regularly, cleansed, transformed, and curated by an ETL tool and in the case of Fusion Analytics placed into the Autonomous Data Warehouse (ADW). An added advantage of this approach is the ability to build up data over time, using historical data for trend analysis.  IT simply exposes the new data to the Business Analyst within OAC, allowing the Business Analyst to leverage it in the same way they do the Fusion data, Figure 9.

Figure 9
Figure 9

IT can develop additional dashboards and data visualizations and simply deliver them out to the Business Analyst and wider user community to consume. This can be considered when there is a need to ensure the governance of the data and security surrounding it are all properly addressed with what might be sensitive and confidential data.

In our example, that maybe survey data to provide a fuller picture of employee and customer satisfaction.

It is not the intention of this blog to consider the pricing implications of these various scenarios. However, it is worth pointing out that Fusion Analytics has been set-up to address all Fusion data storage needs, and you can bring in an additional 50GB of non-Fusion data free into the ADW.

Fusion Analytics is built upon OCI and as such, you can leverage its capabilities, Figure 9 for example shows the use of Oracle Data Integrator as the ETL tool, though of course you could use other tools. ODI is free but requires OCI storage and server to run. However, if you already have Universal Credits, you can simply use those.

Extending the Semantic Model

Within FAW’s OAC there is a Semantic Model that is a business representation of the physical data that provides a presentation layer to the User. The governed, Semantic Model provided by FAW is immutable and is managed by Oracle, ensuring that FAW continues to work as enhancements are delivered over time. However, the Semantic Model can be extended by creating branches to accommodate new functionality. So, once the data has been brought into ADW and modelled, the semantic extensions can be developed to surface that data and so OAC can be used as the single lens for the organisation. Figure 10.

Figure 10
Figure 10

To summarise

We have briefly discussed the various scenarios you might want to consider for bringing in additional data to enrich your analysis and provide richer insights. In our next blog we will discuss how we further to leverage the power of Fusion Analytics, which you can find here.

Duncan Fitter

Director of Product Strategy, Oracle Analytics, Product Management

Duncan Fitter works in Oracle's analytics product strategy team helping customers across the globe achieve their goals through greater insights.

Kiriti Mukherjee

Senior Principal Product Manager, Oracle Analytics, Product Management


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Extending Fusion Analytics - Part 1 of 4

Duncan Fitter | 7 min read

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Extending Fusion Analytics - Part 3 of 4

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