Abstract: In accordance with an embodiment, described herein is a system and method for providing key performance indicator (KPI) customization in an analytic applications environment, which enables data analytics within the context of an organization's enterprise software application or data environment, or a software-as-a-service or other type of cloud or computing environment. The system supports customization derived from multiple layers which, in aggregate, can yield a customized performance metric or KPI object. In accordance with an embodiment, the system supports a user interface with icons that describe original (e.g., out-of-the-box or factory) KPIs and user-modified KPIs. When a user modifies an original KPI object to create a customized KPI, its icon is changed to visibly indicate that the user has modified the KPI. The customized KPI can be used within KPI decks, cards, dashboards, or other types of visualizations; while retaining a lineage to the original KPI object.

Abstract: In accordance with an embodiment, described herein is a system and method for providing a smart help browser extension for use with an analytics environment. An analytic applications environment can be provided by, or otherwise operate at, a computer system providing access to a data warehouse, or data warehouse instance. A smart help browser extension provides a user-interface based, reusable and configurable plugin that can be dynamically configured in order to provide relevant help content. An end-user can be provided with options on how to view the help content, such as via a help bubble of text, an image, or video, for example. The disclosed extension can also provide admins, or other technical users of the analytics environment, with the ability to record custom help content for other (e.g., non-technical) users of the analytics environment.

Abstract: In accordance with an embodiment, described herein is a system and method for providing key performance indicator (KPI) customization in an analytic applications environment, which enables data analytics within the context of an organization's enterprise software application or data environment, or a software-as-a-service or other type of cloud or computing environment. The system supports customization derived from multiple layers which, in aggregate, can yield a customized performance metric or KPI object. In accordance with an embodiment, the system enables creation of a customized KPI, by layering variations of the KPI information on an original (e.g., out-of-the-box or factory) KPI object which are merged at runtime to create the final customized KPI. Each delta-KPI can itself also support multiple, e.g., site/user levels/layers.

Abstract: 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.

Abstract: In accordance with an embodiment, described herein is a system and method for providing key performance indicator (KPI) customization in an analytic applications environment, which enables data analytics within the context of an organization's enterprise software application or data environment, or a software-as-a-service or other type of cloud or computing environment. The system supports customization derived from multiple layers which, in aggregate, can yield a customized performance metric or KPI object. In accordance with an embodiment, the system supports a user interface with icons that describe original (e.g., out-of-the-box or factory) KPIs and user-modified KPIs. When a user modifies an original KPI object to create a customized KPI, its icon is changed to visibly indicate that the user has modified the KPI. The customized KPI can be used within KPI decks, cards, dashboards, or other types of visualizations; while retaining a lineage to the original KPI object.

Abstract: In accordance with an embodiment, described herein is a system and method for providing key performance indicator (KPI) customization in an analytic applications environment, which enables data analytics within the context of an organization's enterprise software application or data environment, or a software-as-a-service or other type of cloud or computing environment. The system supports customization derived from multiple layers which, in aggregate, can yield a customized performance metric or KPI object. In accordance with an embodiment, the system enables creation of a customized KPI, by layering variations of the KPI information on an original (e.g., out-of-the-box or factory) KPI object which are merged at runtime to create the final customized KPI. Each delta-KPI can itself also support multiple, e.g., site/user levels/layers.

Abstract: A cloud-based ETL system provides error detection, error correction and reporting of data integration flows hosted by cloud services. Categories of errors are identified using one or more checks at different points of a data integration flow and one or more actions selected based at least in part on the error category. A determination can be made whether the error category is fault tolerant and one or more actions can be selected based at least in part on the error fault tolerance to correct the error, restart a flow, or generate a notification assisting a user to correct the error.

Abstract: 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.

Abstract: Described herein are systems and techniques for identifying at-risk opportunities and generating a recommendation that can be used by the representatives to help salvage the opportunities. Historical information as well as machine learning algorithms are used to identify the failing opportunities by classifying new and currently in-pursuit opportunities using information from past opportunities to identify which of the new and in-pursuit opportunities might be at risk. Distances between opportunities are estimated based on local neighborhoods determined by relevant variables influencing those opportunities in the local neighborhood. The shortest distance between at risk opportunities and winning opportunities can be identified and utilized to generate the recommendation based on the relevant variables for the shortest path. In some embodiments, an ordered list of actions or changes to actions needed for a successful disposition of the opportunity may be generated and provided to the representative.

Abstract: A cloud-based ETL system provides error detection, error correction and reporting of data integration flows hosted by cloud services. Categories of errors are identified using one or more checks at different points of a data integration flow and one or more actions selected based at least in part on the error category. A determination can be made whether the error category is fault tolerant and one or more actions can be selected based at least in part on the error fault tolerance to correct the error, restart a flow, or generate a notification assisting a user to correct the error.

Abstract: A cloud-based ETL system provides error detection, error correction and reporting of data integration flows hosted by cloud services. Categories of errors are identified using one or more checks at different points of a data integration flow and one or more actions selected based at least in part on the error category. A determination can be made whether the error category is fault tolerant and one or more actions can be selected based at least in part on the error fault tolerance to correct the error, restart a flow, or generate a notification assisting a user to correct the error.

Abstract: A cloud-based ETL system provides error detection, error correction and reporting of data integration flows hosted by cloud services. Categories of errors are identified using one or more checks at different points of a data integration flow and one or more actions selected based at least in part on the error category. A determination can be made whether the error category is fault tolerant and one or more actions can be selected based at least in part on the error fault tolerance to correct the error, restart a flow, or generate a notification assisting a user to correct the error.