Users have come to expect compelling experiences in their modern data applications. Creating these experiences can be challenging and require costly bespoke solutions. Sometimes you want to direct users through the data; in other cases, you want users to explore the data themselves. With Oracle Analytics Cloud (OAC) and our new Semantic Modeling Markup Language (SMML), you can now create a powerful semantic model which acts as a translation layer between your application and your underlying data structures. This semantic model exposes a metrics-oriented data layer that can be used directly in your application via APIs, with embedded visualizations, or in other analytics tools.
Putting your data into the right context
Oracle Analytics offers a wide range of capabilities that provide both governed and self-service analytics. The backbone of these capabilities is an intelligent query engine that provides centralized data access, computes calculations, and enables data governance by creating a pipeline through which anyone can consume information specific to their roles across an enterprise. The query engine is central to data visualizations, dashboards, ad-hoc queries, mobile access, enterprise reporting, data flows, and more. The brains of this query engine is a conceptual data model defined in terms of business semantics — a Semantic Model.
Defining your data
In a decision support ecosystem, a semantic model enables you to structure data in a business-friendly way. It enables you to add business semantics to provide meaning to the data and the governance rules that secure data access. In doing so, it masks the complexity of the underlying data models and data access challenges to analytics consumers, rendering it more sensible to the business user.
Data models are typically specific to their implementation and to their data source type. Most transactional applications data are held in 3NF schemas, data warehouses in dimensional format with facts and dimensions, a data vault with hubs, satellites and links, multi-dimensional data or streaming data..
A well-designed analytics platform should have the capability to consume information in any format or structure and make it available to consumers in a business-friendly view. Most enterprise applications have the semantics for the data defined in the application layer. When bringing in data from these data sources, the semantics needs to be defined in the Analytics system in addition to those for data interaction, calculations, and data governance. The semantic model in Oracle Analytics serves that purpose.
Oracle Analytics has a rich semantic model that enables a developer to build robust, scalable data frameworks needed to support advanced analytics applications across the enterprise. This has been a feature of OAC for many years, powering the robust, scalable applications used by thousands of Oracle Fusion applications
Two great new features to preview
We are excited to share two new developments that will be available as a preview feature in the upcoming release of Oracle Analytics Cloud:
◉ The first is a newly designed, fully browser-based semantic modeler that enables you to create semantic layers on top of federated data sources. Fully compatible with existing enterprise data models that use relational sources in repository document (RPD) format, the new semantic modeler introduces a modern experience that emphasizes team development and version control.
◉ The second one is the Semantic Model Markup Language (SMML), which enables the definition of semantic models using Javascript Object Notation (JSON). Developers have the option to create semantic models using SMML or using the Semantic Modeler with its more familiar diagramming capabilities. The Semantic Modeler in turn generates SMML to define semantic models. With SMML, developers can use any editor to make changes to the semantic model source code or they can use the integrated JSON editor in Semantic Modeler.
The Semantic Modeler has the ability to integrate with any Git-compatible repository, such as GitHub, GitLab, or Git on Oracle Visual Builder. With full support for branching, merging, pull, push, and commit from within Semantic Modeler, multiuser development becomes much less complicated. With Git integration, you have full visibility to a complete change history and the ability to publish to multiple targets.
Compelling data experiences are a key differentiator between good applications and amazing applications. Using a rich semantic model can help your users make the most of their data and provide a seamless, powerful user experience.
Source: oracle.com
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