Oracle International Corporation

Matthew Bedin

Ananth Venkata

Jacques Vigeant

Renu Chintalapati

Saurabh Verma

Balaji Krishnan

Vikas Agrawal

Rajesh Balu

Manisha Gupta

Pavan Ananthamurthy

David Granholm

Naren Chawla

Ashlesh Bajpai

Stefan Schmitz

Joseph Kuttikat

In accordance with an embodiment, described herein is a system and method for providing support for extensibility and customization in an analytic applications environment. An extract, transform, load (ETL) or other data pipeline or process provided by the analytic applications environment, can operate in accordance with an analytic applications schema and/or a customer schema associated with a customer (tenant), to receive data from the customer's enterprise software application or data environment, for loading into a data warehouse instance. A semantic layer enables the use of custom semantic extensions to extend a semantic model, and provide custom content at a presentation layer. Extension wizards or development environments can guide users in using the custom semantic extensions to extend or customize the semantic model, through a definition of branches and steps, followed by promotion of the extended or customized semantic model to a production environment.

System and method for customization in an analytic applications environment

Described herein are techniques for identifying highly relevant content for a user to view in the form of KPI cards and providing the relevant view to the user automatically or by suggestion. The KPIs of highest practical and statistical significance are provided when the user accesses the user interface. In some embodiments, when the user is viewing a KPI, other relevant KPIs may be provided for the user to view as suggestions. Further, in some embodiments, the user may be provided with the KPIs of significance based on anomaly detection, and the explanation for the anomaly as well as suggestions for remedying any issues may be provided to the user. The highly informational content can be surfaced through the use of the advanced machine learning algorithms described herein.

Techniques for data-driven correlation of metrics

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Denver, CO, United States of America

Matthew Bedin