Oracle analytics update adds CX app, semantic modeling tool

New capabilities

The pre-built applications in Fusion Analytics include ERP Analytics, Supply Chain Management (SCM) Analytics and Human Capital Management (HCM) Analytics.

Now, Oracle has added Customer Experience (CX) Analytics.

Oracle Fusion CX Analytics enables finance, marketing, sales and service professionals to monitor customer activity and revenue generation through a set of pre-built KPIs and dashboards, according to the vendor.

Meanwhile, Oracle has added functionality to each of its preexisting Fusion Analytics applications.

ERP Analytics now includes Project Management analytics to analyze ongoing projects; SCM Analytics includes Cost Accounting and Intra/Inter Organizational Transfer analytics to manage cost and inventory; and HCM Analytics includes Diversity, Payroll and Learning analytics to uncover unconscious bias, foster workforce diversity and better manage both employee retention and talent acquisition.

Embedded analytics capabilities built right into Oracle Fusion apps are among the most popular uses of Oracle analytical capabilities, and they put the insights right into the context of decision points within these apps.

The additions are significant for users because they address productivity by giving business users added information within their workflows, according to Doug Henschen, analyst at Constellation Research.

"These embedded analytics capabilities built right into Oracle Fusion apps are among the most popular uses of Oracle analytical capabilities, and they put the insights right into the context of decision points within these apps," he said.

New semantic modeling capabilities in OAC are similarly important, Henschen continued.

Oracle has long offered semantic modeling capabilities, which enable customers to organize data logically based on the type of data and the relationships between data points so data is kept consistent when updated and is easily accessed when developers and data scientists build applications and models.

Those capabilities, however, were available only to data scientists and application developers with deep knowledge of code.

Now, a semantic modeler tool masks the complexity of the underlying data and presents the physical data in a way that opens up its use to a broader base of users. The web-based tool uses a JSON-based Semantic Modeler Markup Language to hide the intricacy of the data and enable more flexible editing and updating of semantic models.

The tool is not for self-service users, but enables more than just a select few within organizations to gain access to semantic models.

In addition, the tool lets more than one user at a time work on a given project with multiuser development capabilities, including version control, and enables continuous integration/continuous delivery as developers build and update applications

"On the Oracle Analytics Cloud side, the democratization of the semantic modeler is the most significant announcement," Henschen said. "It makes it easier for more users to harness data from across organizations to develop consistent and reusable metrics, measures, analyses and analytical applications."

Likewise, James Richardson, Oracle's vice president of product strategy, highlighted the addition of the semantic modeler.

"It brings software development rigor and process to [help organizations] scale analytics," he said. "It's a flexible method for editing and updating a semantic model with multiple contributors. It's going from serial to parallel."

Richardson also noted the importance of new automated insight capabilities in OAC, which is aimed at increasing productivity by enabling self-service users to take action.

Built using augmented intelligence and machine learning, proactive automated insights analyze data sets and automatically develop and deliver data visualizations and explanations of those visualizations to users.

Vendors including Yellowfin and Tableau offer similar automated insight capabilities, providing users with auto-generated dashboards and data narratives that result in insights and action.

"It delivers on the idea of not 'What can I do?' but 'What can this do for me?'" Richardson said. "It's automation of an analytics task that would have taken an analyst hours. This gives people the capability, without going to an analyst or to IT, to iterate more times through a data set."

Beyond the updates throughout Fusion Analytics -- including the launch of CX Analytics -- and additions of the semantic modeler and proactive automated insights, the latest Oracle analytics platform update includes the following:

• new visualizations;
• enhanced AI and machine learning functionality in OAC;
• new data sharing capabilities in Autonomous Data Warehouse, including data from external sources, such as Tableau and Excel;
• a pre-built application with 80 dashboards and 300 KPIs to enable Oracle E-Business Suite users to more quickly gain insight; and
• Oracle Cloud Infrastructure GoldenGate, a streaming analytics tool that enables processing and analyzing of real-time data.

Together, the new capabilities address productivity and reduce reliance on IT, as Oracle intended, according to Henschen.

"The Oracle Fusion Analytics offerings absolutely accomplish this goal because they provide pre-built but configurable content," he said. "[And] the semantic modeler enables data-savvy users and developers to reuse curated data sets, analyses and measures."

Future plans

More additions to Fusion Analytics are part of Oracle's roadmap, according to Richardson. In addition, continuing to build on the theme of doing more for users through automation and augmentation will be a focus.

"[We'll be] doing more for people around their analytics workloads to give them time to make better decisions," Richardson said.

Another focus will be messaging, according to Richardson. Oracle needs to do more to convince potential new customers that it isn't the Oracle of old, which, a few years ago, was viewed as too complex and seemingly out of date, he said.

Now, however, Oracle's analytics platform features many AI and machine learning capabilities and enables both self-service business users, as well as data scientists, and is seen as competitive with peers like Qlik and Tableau.

"The challenge for us is not being well known enough," Richardson said. "It's on us to tell the story more effectively and in a more compelling way. Hopefully, we're getting better at it. Oracle has been in the BI space, and sometimes, we're grouped with [first-generation] BI tools, which doesn't reflect the capabilities we have today."

He added that, as analytics evolves more toward decision intelligence, which is about enabling action through augmentation, he hopes Oracle will be able to attract more notice.

Henschen, meanwhile, said he'd like to see more openness from Oracle.

Generally, Oracle's analytics tools are built to work in concert with other Oracle capabilities rather than mesh with tools from other vendors.

The data sharing capabilities in Autonomous Data Warehouse that include support for Tableau and Excel are indications that Oracle may be embracing more openness, Henschen noted. But, if so, it's only beginning.

"In general, Oracle focuses on Oracle apps, Oracle Cloud Infrastructure and Oracle-centric customers, so openness to third-party tools, sources and solutions is sometimes wanting, [but] there are signs of a more pragmatic, open approach that will benefit customers," he said.