Extending Fusion Analytics - Part 1 of 4

January 10, 2023 | 7 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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Starting your Fusion Analytics extensibility journey…

Welcome to this four-part blog series sharing insight into exploiting Fusion data with Fusion Analytics (FAW) and how to utilise FAW’s power to deliver greater insights beyond those based on Fusion data alone. We will follow an analytics path that many Fusion customers take, exploring the various scenarios they encounter and evaluate on their analytics journey.

What is Fusion Analytics?

Fusion Analytics (Fusion Analytics Warehouse, FAW) is a family of prebuilt, cloud native analytic applications for Oracle Fusion Cloud that provide line of business users with ready-to-use KPIs and insights that improve decision-making. Oracle’s unique breadth and depth of combined analytics and application capabilities enable organizations to unify analytics and provide a single, common view of performance across departments.

Click here to learn more about what FAW has to offer.

FAW is built on top of Oracle Analytics Cloud (OAC) and Autonomous Data Warehouse (ADW) - a powerful combination that provides a flexible platform which helps you address any additional analytical needs, Figure 1. The curated & derived data from Fusion resides in database tables within ADW, the Data Visualizations capabilities of OAC then access this data via the semantic model, which provides a true business orientated view of that data that a Business Analyst can consume.

Figure 1
Figure 1

Analytics is a journey of answering questions and seeking to find out more.

Analytics is not a destination but a journey. Following a HR example, answering the first transactional question, “how many people are leaving?”, leads to the next analytical question, “why are they leaving?”, and the predictive question, “who will leave?”.  This then creates the need to gain further insight in order to act: “let’s identify those high performers at risk of leaving and do something to keep them”.

In this blog series, we will use the concept shown in Figure 2 to explore that journey and the various scenarios that Fusion Analytics can help with.

Figure 2
Figure 2

 

Transactional Reporting – step 0

0. With respect to Fusion, ‘transactional’ insight can be gained with the embedded reporting offered by Oracle Transactional Business Intelligence (OTBI). Fusion Cloud customers take advantage of this at Go-Live and beyond to provide ‘transactional’ or ‘point in time’ insight, (brown box in Figure 2).

Analytics – the ongoing journey…

1. The pale green arrow (Figure 2) represents moving to ‘analytical’ insight with Fusion Analytics (FAW) by leveraging its out-of-box analytical capabilities. Fusion Cloud customers can start early with FAW and as data builds up within their Fusion applications the richness of those insights builds.

2. As Business Analysts start to gain more confidence, many start to take advantage of the power of self-service analytics. They build out analyses of their own, pulling in other data to supplement the Fusion data to gain richer insights (represented by the top green rectangle in Figure 2.)

3. The bottom dark green rectangle (Figure 2) represents the pulling in of additional Fusion data, and/or additional third-party data in a more governed and regular way, along with more powerful customisations. Much of which is delivered with the help of IT or a partner.

Figure 2 is the framework I will use in this blog series to explain the role of Fusion Analytics in that journey – you start with leveraging the out-of-the-box content, extend the KPIs & visualizations, extend the coverage with both additional Fusion & non-Fusion data, undertake further analysis, and implement AI use cases.

Your business priorities should drive your journey…

Though we won’t much spend time here on your FAW implementation and extension approach it should of course be aligned to your business priorities. Starting by taking advantage of what comes out-of-the-box and driving early adoption, ie spending time in steps 1 and 2 above, will ensure a solid beginning to your journey.

So, you may decide that HCM Analytics and within that Workforce Core should be your first functional thread to tackle. Starting with out-of-the-box functionality. You may wish then to build out the KPIs and Visualisations, augment it with some additional Fusion data, then with some external data, then even consider addressing some ML use cases. Then you may decide to tackle the Retention & Turnover, then Talent Acquisition, Talent Profile & Talent Review functional threads. After HCM Analytics or in parallel you may decide to take a similar approach to ERP Analytics. Figure 3.

Figure 3
Figure 3

Alternatively, you may wish to implement both HCM Analytics and ERP Analytics simultaneously and start using the out-of-the-box functionality, and then take a similar approach to extending it as above from there, Figure 4.

Figure 4
Figure 4

In this blog series we will explore just one of these threads, as shown in Figure 2, versus specifically how your business priorities might impact that overall implementation approach. We will discuss the various extensibility scenarios that are available and not dwell too long on the considerable benefits Fusion Analytics delivers through its pre-built out-of-the-box content. However, let’s start at the beginning.

Starting the journey, exploiting what comes out-of-the-box with Fusion Analytics

Fusion Analytics has a large amount of out-of-the-box KPIs and data visualizations that a Business Analyst can exploit, and it is very easy for them to tailor them to their own requirements. For example, changing a pie chart on a KPI to a line graph, or changing the thresholds of the KPI. They can build additional KPIs based on the thousands of metrics that are available and subsequently monitor the aspects of the business that they deem important.

The vastness and completeness that this out-of-the-box content can offer is often enough for many Business Analysts across the various departments that Fusion Analytics covers. This content is continuing to be developed, enriched, and delivered out to customers which each new release of Fusion Analytics.

If you’re interested in understanding the pre-built and out-of-the-box content that Fusion Analytics has to offer then read my blog on the subject here.

Behind the scenes, data is regularly pulled from Fusion Cloud by the Data Pipeline and this curated and derived data then resides in the Oracle Autonomous Data Warehouse. Oracle Analytics Cloud then provides the Business Analyst with access to the KPIs and Data Visualisations via a semantic model, Figure 5.

Figure 5
Figure 5

Using the front-end (OAC) to explore the data further….

With the full power of Oracle Analytics Cloud (OAC) at their disposal, a Business Analyst can take advantage of its self-service analytics capabilities to both shape existing and create many more data visualizations to further explore the Fusion data. OAC enables the visual exploration of the Fusion data, via OAC’s sematic model, to create and share compelling stories. A Business Analyst can then discover the signals in Fusion data that can turn complex relationships into meaningful, and easy-to-understand communications through the creation of engaging visualizations.

To learn more about Data Visualization, look here.

Example: as an HR Manager you may track other KPIs and wish to build additional visualizations to better understand employee movement across the organisation and its impact on employee satisfaction.

Augmenting insights with extra Fusion data…

The data pipeline has been created to pull in the Fusion data needed to answer all the core questions that a business might want to ask. In some scenarios, you may have additional Fusion data specific to your Business Analyst’s needs.  We have created an easy-to-use Business Analyst friendly framework that provides the ability to easily augment the exiting Fusion data with other Fusion data. Descriptive Flexfields is one such example of data that you might want to bring in, Figure 6. A blog on enabling it with Fusion Analytics can be found here.

Example: from a HR perspective you may wish to bring in additional employee engagement data that you have within Fusion that is not already pulled across by FAW.

Figure 6
Figure 6

Summarising these early days of your analytics journey…

Use the embedded OTBI in Fusion to provide transactional insight, use out-of-the-box Fusion Analytics to both deepen & broaden that insight across pillar. The experience can be tailored by tweaking and creating more KPIs and Dashboards (Data Visualizations), to easily bring in more Fusion Data to supplement and enhance your analytics.

And next in our journey is a blog on delivering deeper insights through exploring the value of what the combination of Fusion data with non-Fusion data can deliver, 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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