SYSTEM AND METHOD FOR PROVIDING TIERED KPI CUSTOMIZATION IN AN ANALYTICAL APPLICATION ENVIRONMENT - Patent application

Abstract

According to one embodiment, described herein are systems and methods for providing key performance indicator (KPI) customization in an analytical application environment, which enables data analytics within the context of an organization's enterprise software application or data environment, or software-as-a-service or other types of cloud or computing environments. The system supports customization derived from multiple layers, which, taken together, can result in a customized performance metric or KPI object. According to one embodiment, the system enables the creation of customized KPIs by layering variations of KPI information about original (e.g., out-of-the-box or factory) KPI objects that are merged at runtime to create the final customized KPI. Each delta-KPI itself may also support multiple, e.g., site / user levels / layers. This approach can be used to provide extensibility for user interface decks / dashboards in which KPI visualization objects appear, such as decks, cards, dashboards, or other types of visualizations.

Description

[Technical Field]

[0001] Copyright Notice A portion of the disclosure of this patent document contains material that is subject to copyright protection. As the patent document or patent disclosure is publicly disclosed in the U.S. Patent and Trademark Office patent files and records, the copyright owner has no objection to the copying thereof by anyone, but otherwise reserves all copyright rights whatsoever without exception.

[0002] Priority claim: This application claims priority to U.S. provisional patent application Ser. No. 63 / 083,320, filed September 25, 2020, entitled "SYSTEM AND METHOD FOR PROVIDING LAYERED KPI CUSTOMIZATION IN AN ANALYTIC APPLICATIONS ENVIRONMENT"; U.S. patent application Ser. No. 17 / 476,242, filed September 15, 2021, entitled "SYSTEM AND METHOD FOR PROVIDING A USER INTERFACE FOR KPI CUSTOMIZATION IN AN ANALYTIC APPLICATIONS ENVIRONMENT"; and U.S. patent application Ser. No. 17 / 476,246, filed September 15, 2021, entitled "SYSTEM AND METHOD FOR PROVIDING A USER INTERFACE FOR KPI CUSTOMIZATION IN AN ANALYTIC APPLICATIONS ENVIRONMENT." This application is related to a U.S. patent application entitled "METHOD FOR ANALYTIC APPLICATIONS ENVIRONMENT," filed May 6, 2020, serial number 16 / 868,081, and published as U.S. Patent Application Publication No. 20200356575; each of these applications is incorporated herein by reference.

[0003] Technical fields: FIELD Embodiments described herein relate generally to computer-based methods for providing computer data analytics and business intelligence data, and more particularly to systems and methods for providing key performance indicator (KPI) customization in an analytical application environment. [Background technology]

[0004] background Generally described, within an organization, data analytics enables the computer-based examination or analysis of large amounts of data in order to draw conclusions or other information from that data, and business intelligence tools provide an organization's business users with information that describes enterprise data in a format that enables strategic business decisions to be made.

[0005] There is growing interest in developing software applications that leverage the use of data analytics in conjunction with an organization's enterprise software application / data environment (e.g., an Oracle Fusion Applications environment or other type of enterprise software application / data environment) or in conjunction with a Software-As-A-Service (SaaS) or cloud environment (e.g., an Oracle Analytics Cloud or Oracle Cloud Infrastructure environment or other type of computing cloud environment). Summary of the Invention [Problem to be solved by the invention]

[0006] Some analytics environments support the use of dashboards, key performance indicators (KPIs), or other types of reports. However, different customers of a data analytics environment may have different preferences regarding how their data is categorized, aggregated, or transformed for the purposes of providing such KPIs or other business intelligence data. [Means for solving the problem]

[0007] overview: According to certain embodiments, described herein are systems and methods for providing key performance indicator (KPI) customization in an analytical application environment that enables data analytics within the context of an organization's enterprise software application or data environment, or software as a service or other type of cloud or computing environment. The system supports customization derived from multiple layers that, collectively, can result in customized performance metrics or KPI objects.

[0008] According to one embodiment, the system enables the creation of customized KPIs by layering variations of KPI information about original (e.g., out-of-the-box or factory) KPI objects that are merged at runtime to create the final customized KPI. Each delta-KPI itself may also support multiple, e.g., site / user levels / layers. This approach can be used to provide extensibility for user interface decks / dashboards where KPI visualization objects appear, such as decks, cards, dashboards, or other types of visualizations.

[0009] According to one embodiment, the system supports a user interface with icons that describe the 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, the icon changes to visually indicate that the user has modified the KPI. The customized KPI can be used within a KPI deck, card, dashboard, or other type of visualization while retaining its lineage to the original KPI object. [Brief explanation of the drawings]

[0010] [Figure 1] 1 illustrates a system for providing an analytical application environment, according to one embodiment. [Figure 2] 1 illustrates a system for supporting extensibility and customization in an analytical application environment, according to one embodiment. [Figure 3] 1 illustrates how the system can be used to provide KPI customization according to one embodiment. [Figure 4] 1 illustrates an exemplary KPI customization according to one embodiment. [Figure 5] FIG. 2 illustrates exemplary metadata according to one embodiment. [Figure 6] 10 further illustrates an exemplary KPI customization according to one embodiment. [Figure 7] FIG. 10 illustrates another exemplary metadata according to one embodiment. [Figure 8] 10 further illustrates an exemplary KPI customization according to one embodiment. [Figure 9] FIG. 1 illustrates a set of exemplary operations for retrieving data associated with a KPI, according to one embodiment. [Figure 10] FIG. 1 illustrates an exemplary merged JSON file, according to one embodiment. [Figure 11] 1 illustrates a process for providing KPI customization in an analytical application environment, according to one embodiment. [Figure 12] FIG. 1 illustrates an exemplary user interface that allows a user to create and use customized KPIs, according to an embodiment. [Figure 13] FIG. 1 illustrates an exemplary user interface that allows a user to create and use customized KPIs, according to an embodiment. [Figure 14] FIG. 1 illustrates an exemplary user interface that allows a user to create and use customized KPIs, according to an embodiment. [Figure 15] FIG. 1 illustrates an exemplary user interface that allows a user to create and use customized KPIs, according to an embodiment. [Figure 16] FIG. 1 illustrates an exemplary user interface that allows a user to create and use customized KPIs, according to an embodiment. [Figure 17] FIG. 1 illustrates an exemplary user interface that allows a user to create and use customized KPIs, according to an embodiment. [Figure 18] FIG. 1 illustrates an exemplary user interface that allows a user to create and use customized KPIs, according to an embodiment. [Figure 19] FIG. 1 illustrates an exemplary user interface that allows a user to create and use customized KPIs, according to an embodiment. [Figure 20] FIG. 1 illustrates an exemplary user interface that allows a user to create and use customized KPIs, according to an embodiment. [Figure 21] FIG. 1 illustrates an exemplary user interface that allows a user to create and use customized KPIs, according to an embodiment. [Figure 22] FIG. 1 illustrates a process for providing KPI customization in an analytical application environment according to an embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0011] Detailed Description: As discussed above, within an organization, data analytics enables the computer-based examination or analysis of large amounts of data in order to draw conclusions or other information from that data, and business intelligence tools provide an organization's business users with information that describes enterprise data in a format that enables them to make strategic business decisions.

[0012] There is growing interest in developing software applications that leverage the use of data analytics in connection with an organization's enterprise software application / data environment (e.g., an Oracle Fusion Applications environment or other type of enterprise software application / data environment) or in connection with a Software-As-A-Service (SaaS) or cloud environment (e.g., an Oracle Analytics Cloud or Oracle Cloud Infrastructure environment or other type of cloud or computing environment).

[0013] According to certain embodiments, described herein are systems and methods for providing key performance indicator (KPI) customization in an analytical application environment that enables data analytics within the context of an organization's enterprise software application or data environment, or software as a service or other type of cloud or computing environment. The system supports customization derived from multiple layers that, collectively, can result in customized performance metrics or KPI objects.

[0014] According to one embodiment, the system enables the creation of customized KPIs by layering variations of KPI information about original (e.g., out-of-the-box or factory) KPI objects that are merged at runtime to create the final customized KPI. Each delta-KPI itself may also support multiple, e.g., site / user levels / layers. This approach can be used to provide extensibility for user interface decks / dashboards where KPI visualization objects appear, such as decks, cards, dashboards, or other types of visualizations.

[0015] According to one embodiment, the system as a whole supports customization derived from multiple layers that can result in customized performance metrics or KPI objects that do not modify the underlying or original (e.g., out-of-the-box or factory) versions of the KPI objects, and allows for upgrades, reversions, and tracking of changes in the KPI editor or user interface.

[0016] According to one embodiment, customers can move data, create key performance indicators (KPIs), and present them as decks, cards, dashboards, or other types of visualizations. Occasionally, customers may want to customize and extend those KPIs for use in their particular business, which traditionally would require a "save as" approach to creating a new KPI, but the lineage back to the original KPI would be lost. By layering variations of KPI information onto the original (e.g., out-of-the-box or factory) KPI object, this feature is particularly useful, for example, in multi-tenant environments, where tenants can layer modifications to the base KPI plus tenant-specific or user-specific delta KPIs, which are merged at runtime to create the final customized KPI.

[0017] According to one embodiment, the system supports a user interface with icons that describe the 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, the icon changes to visually indicate that the user has modified the KPI. The customized KPI can be used within a KPI deck, card, dashboard, or other type of visualization while retaining its lineage to the original KPI object.

[0018] According to an embodiment, at any stage, the user can revert back to the available or factory KPIs without their pre-configuration. The lineage of the customized KPI to the original KPI also allows it to be patched or otherwise updated when the original KPI is updated.

[0019] According to various embodiments, technical advantages of the described approach include, for example, (1) optimization of the storage required for creating and using KPIs, since out-of-the-box or factory KPI objects often require only moderate fine-tuning, and (2) ease of supportability and upgradeability of the underlying factory KPI definitions across subsequent releases.

[0020] Analytical Application Environment According to an embodiment, a data warehouse environment or component, such as, for example, an Oracle Autonomous Data Warehouse (ADW), an Oracle Autonomous Data Warehouse Cloud (ADWC), or any other type of data warehouse environment or component adapted to store large amounts of data, can provide a central repository for storing data collected by one or more business applications.

[0021] For example, according to an embodiment, a data warehouse environment or component may be provided as a multidimensional database employing OLAP (Online Analytical Processing) or other techniques to generate business-related data from data from multiple disparate sources. An organization may extract such business-related data from one or more vertical and / or horizontal business applications and inject the extracted data into a data warehouse instance associated with the organization.

[0022] Horizontal business applications include ERP, HCM, CX, SCM, and EPM, as mentioned above, and can provide a wide range of functions across various corporate organizations.

[0023] Vertical applications are generally narrower in scope than horizontal applications, but provide access to a set of data up or down within a defined area or industry, such as medical software or banking software for use within a particular organization.

[0024] Software vendors are increasingly offering enterprise software products or components, such as Oracle Fusion Applications, as SaaS or cloud-oriented offerings, while other enterprise software products or components, such as Oracle ADWC, may be offered as one or more of SaaS, Platform-as-a-Service (PaaS), or hybrid subscriptions. Enterprise users of traditional business intelligence (BI) applications and processes are typically faced with the task of extracting data from horizontal and vertical line of business applications and putting the extracted data into a data warehouse, a process that can require both significant time and resources.

[0025] According to an embodiment, the analytical application environment enables customers (tenants) to develop computer-executable software analytical applications for use with BI components, such as, for example, an OBIA (Oracle Business Intelligence Applications) environment or other types of BI components adapted to examine large amounts of data obtained by the customers (tenants) themselves or from multiple third-party entities.

[0026] For example, according to an embodiment, the analytical application environment may be utilized to pre-populate the reporting interface of a data warehouse instance with relevant metadata describing business-related data objects associated with various business productivity software applications, to include, for example, pre-defined dashboards, key performance indicators (KPIs), or other types of reports.

[0027] According to an embodiment, an analytics application environment may be provided in connection with an analytics cloud environment (analytics cloud), such as, for example, the Oracle Analytics Cloud (OAC) environment, which provides a scalable and secure public cloud service that provides the ability to explore and perform collaborative analytics.

[0028] FIG. 1 illustrates a system for providing an analytical application environment, according to one embodiment.

[0029] 1 is provided for the purpose of illustrating an example of one type of data analytics environment that may utilize various embodiments of KPI customization as described herein. According to other embodiments and examples, the KPI customization functionality described herein may be used with other types of data analytics environments.

[0030] As shown in FIG. 1 , according to an embodiment, the analytical application environment 100 may be provided by or operate on a computer system having computer hardware (e.g., processor, memory) 101, one or more software components operating as a control plane 102 and a data plane 104, and providing access to a data warehouse or data warehouse instance 160.

[0031] According to embodiments, the components and processes illustrated in FIG. 1 and further described with respect to various other embodiments may be provided as software or program code executable by a computer system or other type of processing device. For example, according to embodiments, the components and processes described herein may be provided by a cloud computing system or other suitably programmed computer system.

[0032] According to an embodiment, the control plane operates to control cloud or other software products offered in connection with a SaaS or cloud environment, such as, for example, an Oracle Analytics Cloud or Oracle Cloud Infrastructure environment, or other type of cloud or computing environment. For example, according to an embodiment, the control plane may include a console interface 110 that allows access by a client computing device 10 having device hardware 12, applications 14, and a user interface 16 under the control of a customer (tenant) and / or cloud environment having provisioning components 111.

[0033] According to embodiments, the console interface may enable access by customers (tenants) operating a graphical user interface (GUI) and / or a command line interface (CLI) or other interface, and / or may include an interface for use by a provider of a SaaS or cloud environment and its customers (tenants). For example, according to embodiments, the console interface may provide an interface that allows a customer to provision services for use within the customer's SaaS environment, and an interface that allows the customer to configure those provisioned services.

[0034] According to an embodiment, a customer (tenant) can request provisioning of a customer schema 164 within the data warehouse. The customer can also provide multiple attributes associated with the data warehouse instance via a console interface, including required attributes (e.g., login credentials) and optional attributes (e.g., size or speed). A provisioning component can then provision the requested data warehouse instance including the data warehouse customer schema and populate the data warehouse instance with the appropriate customer-provided information.

[0035] Additionally, according to an embodiment, the provisioning component can be utilized to update or edit the data warehouse instance and / or the ETL processes operating in the data plane, for example, by changing or updating the requested frequency of ETL process execution for a particular customer (tenant).

[0036] According to embodiments, the data plane API can communicate with the data plane. For example, according to embodiments, provisioning and configuration changes for services provided by the data plane can be communicated to the data plane via the data plane API.

[0037] According to an embodiment, the data plane may include a data pipeline / processing layer 120 and a data transformation layer 134. Together, the data pipeline / processing layer 120 and the data transformation layer 134 process operational or transactional data from an organization's enterprise software application / data environment, such as, for example, business productivity software applications provisioned in a customer's (tenant's) SaaS environment. The data pipeline / processing may include various functions that extract transactional data from business applications and databases provisioned in the SaaS environment and then load the transformed data into a data warehouse.

[0038] According to an embodiment, the data transformation layer may include data models, such as knowledge models (KMs) or other types of data models, that the system utilizes to transform transactional data received from business applications provisioned in the SaaS environment and corresponding transactional databases into a model format understood by the analytical application environment. The model format may be provided in any data format suitable for storage in a data warehouse. According to an embodiment, the data plane may also include a data / configuration user interface 130 and a mapping / configuration database 132.

[0039] According to an embodiment, the data warehouse may include a default analytics application schema (referred to herein, according to some embodiments, as an analytics warehouse schema) 162 and customer schemas, as described above, for each customer (tenant) of the system.

[0040] According to an embodiment, the data plane is responsible for performing ETL (extract, transform, load) operations, which include extracting transactional data from an organization's enterprise software application / data environment, such as business productivity software applications and corresponding transactional databases offered in a SaaS environment, transforming the extracted data into a model format, and loading the transformed data into customer schemas in a data warehouse.

[0041] For example, according to an embodiment, each customer (tenant) of the environment may be associated with its own customer tenancy within the data warehouse. The customer tenancy may be associated with its own customer schema and may additionally be provided with read-only access to analytical application schemas. The analytical application schemas may be updated periodically or otherwise by data pipelines / processes, e.g., ETL processes.

[0042] According to an embodiment, the data pipeline / processing may be scheduled to extract transactional data at regular intervals (e.g., hourly / daily / weekly) from an enterprise software application / data environment, such as, for example, a business productivity software application and corresponding transaction database 106 provisioned in a SaaS environment.

[0043] According to embodiments, an extraction process 108 can extract transactional data, which, once extracted, can be inserted into a data staging area by a data pipeline / processing. The data staging area can serve as a temporary staging area for the extracted data. Data quality and data protection components can be used to ensure the integrity of the extracted data. For example, according to embodiments, a data quality component can validate the extracted data while it is temporarily held in the data staging area.

[0044] According to an embodiment, once the extraction process completes the extraction, a data transformation layer can be used to initiate a transformation process that changes the extracted data into a model format for loading into a customer schema in a data warehouse.

[0045] As described above, according to embodiments, the data pipeline / processing can work in conjunction with a data transformation layer to transform data into a model format. A mapping / configuration database can store metadata and data mappings that define the data model used by the data transformation. A data / configuration user interface (UI) can facilitate access and modification of the mapping / configuration database.

[0046] According to an embodiment, the data transformation layer can transform the extracted data into a format suitable for loading into a data warehouse customer schema, for example, according to a data model such as those described above. During the transformation, the data transformation can create dimensions, create facts, and create aggregates, as appropriate. Creating dimensions can include creating dimensions or fields for loading into the data warehouse instance.

[0047] According to an embodiment, after transforming the extracted data, the data pipeline / processing can execute a warehouse load procedure 150 to load the transformed data into a customer schema instance of the data warehouse. Following loading the transformed data into the customer schema, the transformed data can be analyzed and utilized in a variety of additional business intelligence processes.

[0048] According to certain embodiments, an illustrative example of an analytical application environment that may utilize the various systems, methods, and features described herein is set forth in U.S. patent application entitled "SYSTEM AND METHOD FOR CUSTOMIZATION IN AN ANALYTIC APPLICATIONS ENVIRONMENT," filed May 6, 2020, serial number 16 / 868,081, published as U.S. Patent Application Publication No. 20200356575, which is incorporated herein by reference. According to various embodiments, the systems and methods described herein may be used with other types of enterprise software application or data environments, cloud environments, cloud services, cloud computing, or other analytical application or computing environments.

[0049] Extensibility and Customization Different customers in data analytics environments may have different requirements regarding how data is classified, aggregated, or transformed for the purposes of providing data analytics or business intelligence data or for the purposes of developing software analytics applications.

[0050] To support such different requirements, according to one embodiment, the system may include a semantic layer that enables extending the semantic data model (semantic model) using custom semantic extensions to provide custom content at the presentation layer. An extension wizard or development environment can guide a user in extending or customizing the semantic model through the definition of branches and steps using custom semantic extensions, and then promoting the extended or customized semantic model to a production environment.

[0051] FIG. 2 illustrates a system for supporting extensibility and customization in an analytical application environment according to one embodiment.

[0052] According to one embodiment, the semantic layer may include data that defines a semantic model of a customer's data, which is useful in helping users understand and access that data using commonly understood business terms.

[0053] 2, according to one embodiment, semantic layer 230 may include a packaged semantic model 232 that can be used to provide packaged content. For example, the system may use the ETL or other data pipelines or processes described above to load data from a customer's enterprise software application or data environment into a data warehouse instance, and then use the packaged semantic model to provide the packaged content to the presentation layer.

[0054] According to one embodiment, the semantic layer may also be associated with one or more semantic extensions 236 that can be used to extend the packaged semantic model to provide custom content to the presentation layer 240.

[0055] According to one embodiment, the presentation layer can enable access to the data content using, for example, software analytics applications, user interfaces, dashboards, key performance indicators (KPIs) 242, or other types of reports or interfaces that may be provided by products such as Oracle Analytics Cloud or Oracle Analytics for Applications.

[0056] For example, as described below, according to one embodiment, a customized KPI may be created by combining or merging various levels of extensions, including original, factory, or out-of-the-box available KPI definitions 302 and customer extensions 304, to create a resulting or customized KPI card 306.

[0057] According to one embodiment, in addition to data sourced from customer environments using the ETL or other data pipelines or processes described above, customer data can be loaded into the data warehouse instance using a variety of data models or scenarios that provide opportunities for further extensibility and customization.

[0058] Layered KPI customization According to one embodiment, the system as a whole supports customization derived from multiple layers that can result in customized performance metrics or KPI objects that do not modify the underlying or original (e.g., out-of-the-box or factory) versions of the KPI objects, and allows for upgrades, reversions, and tracking of changes in the KPI editor or user interface.

[0059] According to one embodiment, customers can move data, create key performance indicators (KPIs), and present them as decks, cards, dashboards, or other types of visualizations. Occasionally, customers may want to customize and extend those KPIs for use in their particular business, which traditionally would require a "save as" approach to creating a new KPI, but the lineage back to the original KPI would be lost. By layering variations of KPI information onto the original (e.g., out-of-the-box or factory) KPI object, this feature is particularly useful, for example, in multi-tenant environments, where tenants can layer modifications to the base KPI plus tenant-specific or user-specific delta KPIs, which are merged at runtime to create the final customized KPI.

[0060] FIG. 3 illustrates how the system may be used to provide KPI customization according to one embodiment in which KPI definitions may be merged with extensions to provide customized KPIs.

[0061] As described above, according to one embodiment, in an analytical application environment, the presentation layer may enable access to data content using, for example, a software analytical application, a user interface, a dashboard, key performance indicators (KPIs), or other types of reports or interfaces, such as may be provided by products such as Oracle Analytics Cloud or Oracle Analytics for Applications. In such an environment, KPI customization allows customers to leverage the same underlying factory KPIs that, for example, Oracle experts provide as part of Fusion Applications or the Fusion Applications Warehouse (FAW).

[0062] 3, according to one embodiment, this approach follows a multi-level or multi-layer approach to KPI customization, which results in customized KPIs that, as a whole, do not touch the underlying Oracle version, for example. This allows for upgrades, reversions, and tracking of changes in, for example, the KPI editor or other user interfaces.

[0063] Layered, customized data model According to one embodiment, the system provides separation at the data model level between original (eg, out-of-the-box or factory) versions of KPI objects and customized KPI objects.

[0064] For example, according to an embodiment, a CXO_MDS_KPI table may be provided that includes out-of-the-box or factory versions of multiple KPI objects. In such an example, a CXO_MDS_KPI_C table may then be provided that includes customizations to one or more of those KPI objects, e.g., as fully customized KPI objects or as customizations to the out-of-the-box or factory versions of the KPI objects.

[0065] According to one embodiment, customer data can be accessed through a base table containing KPI objects that are shipped out-of-the-box (i.e., from the factory or system provider). A read-only copy can be provided to this table, and there are no inserts, updates, or deletes to this table by application code. Those KPI objects developed in the factory are imported into this table, for example, during system (pod) provisioning. The base table is not striped by tenant, so there is only one copy of the factory metadata for the entire system (pod), and the table is not replicated per tenant.

[0066] According to one embodiment, when a user creates a new KPI object or customizes the original (e.g., out-of-the-box or factory) version of a KPI object, the system saves this addition / customization in a custom table.

[0067] For example, in a multi-tenant analytic application environment, a first tenant may create a first set of changes to a pre-configured, available or factory version of a KPI object, which first set of changes are stored as a first delta KPI. A second tenant may create a different / second set of changes to a pre-configured, available or factory version of a KPI object, which second set of changes are stored as a different / second delta KPI.

[0068] According to one embodiment, the system does not modify the original (e.g., out-of-the-box or factory) version of the KPI object or copy the object into the tenant's stored data space, as this would be redundant and would limit the system's ability to link customized KPIs, based on delta KPIs, back to the original out-of-the-box or factory KPI objects.

[0069] According to one embodiment, the custom table is striped and each customer customization is stored in a separate stripe. For new KPI objects, the entire metadata may be stored in the custom table. For customizations of factory KPI objects, the delta KPI metadata may be stored in the custom table.

[0070] According to one embodiment, the customized KPIs may be stored in a JSON format, such as the example shown below, which may then be used to render a visualization of the KPIs in a user interface.

[0071] According to one embodiment, each KPI may be associated with an ID, a namespace, metadata, and an access control list (ACL) ID that indicates the particular KPI.

[0072] For example, the ID may be provided as a numeric value, and the namespace may indicate the source of the KPI or delta KPI object. The metadata may indicate definitions of various dimensions, formulas, or other information associated with the customer data that will be queried to provide the resulting KPI visualization, for example, as shown in Exemplary Metadata 1 below. The ACL ID may be used to provide an indication of the security required to access the KPI.

[0073] Example explanation of KPI customization scenario Various examples of different KPI customization scenarios are provided below, according to an embodiment.

[0074] 4 illustrates an example KPI customization according to one embodiment that may merge a KPI definition with an extension to provide a customized KPI. As shown in FIG. 4 and reproduced in part below, in this example, the original (e.g., out-of-the-box or factory) version of the KPI object is not customized:

[0075] [Table 1]

[0076] In this example, as described above, an out-of-the-box or factory version of a KPI object may be used to access customer data and generate KPI decks, cards, dashboards, or other types of visualizations based on that data.

[0077] 5 is a diagram illustrating exemplary metadata according to one embodiment showing a KPI definition associated with an out-of-the-box or factory version of a KPI object. As shown in FIG. 5 and reproduced below, in this example, the KPI provides workforce information, including country location and region, for use in generating the KPI.

[0078]

number

[0079] In this example, the metadata may be used to access customer data and generate KPI decks, cards, dashboards, or other types of visualizations based on that data, including information based on the country or region dimension (but in this example, not based on the city dimension).

[0080] KPI Customization - Adding a New Dimension 6 further illustrates an example KPI customization according to one embodiment that may merge a KPI definition with extensions to provide a customized KPI. As shown in FIG. 6 and partially reproduced below, in this example, an out-of-the-box or factory version of a KPI object is customized, e.g., new dimensions are added to the KPI:

[0081] [Table 2]

[0082] In this example, modifications to the original (e.g., out-of-the-box or factory) version of a KPI object, i.e., delta-KPI, are<delta metadata> , as well as layer IDs and stripe IDs that can be used to support layered KPI customization and customization associated with different tenants.

[0083] For example, according to one embodiment, a layer ID can be used as a site identifier to indicate site layer customization. In another example, a layer ID can be used as a department identifier to indicate department layer customization. Other types of layer IDs can be used to indicate, for example, user layer or other levels of customization.

[0084] As described herein, according to an embodiment, a multi-level or multi-layer approach or design to KPI customization can be extended to include any number of additional layers of customization. For example, a layer ID can be used to indicate any layer that is meaningful to the customer, such as a corporate enterprise region (e.g., US, Europe), a department (e.g., HR, Finance), or a particular user or group of users.

[0085] According to one embodiment, a stripe ID may be used to indicate a tenant, for example, in a cloud or multi-tenant environment, allowing a particular table for use in such an environment to be shared by multiple tenants.

[0086] According to one embodiment, the ACL for a delta KPI may be configured to be different from that associated with the underlying KPI, allowing, for example, different departments to use different ACLs, and the KPI will be returned appropriately depending, for example, on the ACL attributes of the department or user accessing the customized KPI.

[0087] FIG. 7 is a diagram illustrating another example metadata illustrating KPI definitions associated with out-of-the-box or factory versions of KPI objects, according to one embodiment.

[0088] 7 and reproduced below, in this example using the delta-KPI definition available with no pre-configuration of the KPI object or associated with the factory version, the user has added a dimension for city. The KPI has effectively been customized, and thus the combined (KPI + delta-KPI) metadata may be used to access customer data and generate KPI decks, cards, dashboards, or other types of visualizations based on that data, including information based on the country, region, and / or city dimensions added in this example by the delta-KPI customization.

[0089]

number

[0090] In this example, the original KPI metadata provided by the out-of-the-box or factory version of the KPI object and directed to a country or region is not repeated in the delta KPI metadata. However, when a query is made against the customer data to generate a KPI deck, card, dashboard, or other type of visualization, the system will include both the country information represented in the original KPI metadata and the city information represented in the delta KPI metadata to process the query.

[0091] Because the original out-of-the-box or factory version of a KPI object is not modified, if any changes are made to the original KPI, for example by Oracle, the original KPI will continue to function, and as long as the delta KPIs do not conflict with the underlying factory KPI, those delta KPIs will continue to function as well, plus can benefit from the original KPI being updated, patched, or otherwise modified.

[0092] KPI Customization - Creating new customized KPIs 8 further illustrates an exemplary KPI customization according to one embodiment that may merge KPI definitions with extensions to provide a customized KPI. As shown in FIG. 8 and partially reproduced below, in this example, a new customized KPI is created, optionally, but not necessarily, starting with an available, unconfigured or factory version of the KPI object as a starting point.

[0093] [Table 3]

[0094] In this example showing a new customized KPI, the customer did not create delta KPI metadata when creating the new KPI, but instead created a new KPI (in this example in the namespace "Admin"). In this example, KPI ID=3 indicates that the KPI is a new customized KPI, not a delta KPI. Additionally, in this example, <metadata>The layer is null in this instance because, again, it is not a delta KPI but a new KPI customization (optionally starting with a pre-configured, available or factory version of the KPI object as a starting point).

[0095] In this example, the KPI is also created for a specific tenant ("Tenant1"). Each delta KPI is created as a delta of the original (e.g., out-of-the-box or factory) version of the KPI object.

[0096] Although not shown above, according to some embodiments, a customer / tenant may, for example, take a KPI ID3 delta-KPI and then create further / additional delta-KPIs, and the process may continue for other layers. Additional layer values ​​and / or column types may also be used to provide further layering or customization.

[0097] For example, according to one embodiment, to support user-level customization, an object may include additional customer, user, or other columns. Alternatively, user-level customization may be achieved by, for example, layer=USER, and layer=ID-<name of user> (user's name). Similarly, the layer may be indicated as layer=CUSTOM or some other value to indicate some other customization layer. The stripe ID may be used, for example, to indicate a department (which may be associated with that user).

[0098] According to one embodiment, the above-described KPI model may be used in connection with the presentation layer of the data analytics environment, for example, to prepare user interface decks, cards, dashboards, or other visualizations associated with customer data and maintained within the data analytics environment.

[0099] For example, according to one embodiment, the dimensions indicated by the KPI object metadata as described above may be used by a data analytics environment while accessing a database via a semantic model or layer.

[0100] According to other embodiments, instead of accessing data through a semantic model or layer, the system may access data through some other model or layer, for example, by directly accessing the data itself or through some other intermediate component that provides access to customer data and supports searching of data according to KPI objects and / or customized KPI objects.

[0101] Example of operation According to one embodiment, at runtime, when creating a visualization associated with a particular KPI, the system consults the definition of the KPI provided by the KPI object (including any delta KPIs, if appropriate), as described above, and uses that information to generate operations, such as SQL SELECT operations or other commands, to retrieve data from the database, for example, using a combination of read, insert, update, or join across various such operations. According to one embodiment, various examples of READ, INSERT, UPDATE, and DELETE operations are provided below.

[0102] READ operation According to an embodiment, a READ operation may retrieve data associated with a KPI from a database using pseudo-SQL logic or other data retrieval processes. In the following example, the table includes factory KPIs (not customized by a tenant, similar to the example shown as KPI1 above); fully customized KPIs (similar to the example shown as KPI3 above); and factory-customized KPIs (similar to the example shown as KPI2 above).

[0103] 9 is a diagram illustrating an exemplary set of operations for retrieving data associated with a KPI, according to one embodiment. As shown in FIG. 9 and reproduced below, in this example:

[0104]

number

[0105] 10 shows an example merged JSON file according to one embodiment that includes additional properties at each KPI attribute level to indicate which attributes are customized versus factory-provided attributes. As illustrated in FIG. 10 and reproduced below, in this example:

[0106]

number

[0107] According to one embodiment, the data returned from the database using the above process needs to be further processed before providing the data to the presentation layer or user interface. For example, the KPIs, f_metadata, and c_metadata_site in the "FACTORYCUSTOM" set (310) would be compared, merged, and processed according to the supported customization use case. Using the example above where the factory model includes country but then adds city delta, the JSON would then include all three of the dimensions specified by the KPI object—the available or factory version and the customized delta—of the KPI object.

[0108] According to an embodiment, the JSON information may then be used to provide the information returned by the database to a user interface. The JSON may also indicate, for example, when the data associated with a particular KPI is provided by the original (e.g., out-of-the-box or factory) version of the KPI object or by a customized KPI object.

[0109] According to one embodiment, such information may then be analyzed by the presentation layer or user interface when rendering an indication of the KPI (e.g., including its icon as displayed in the user interface) to indicate whether the icon (and its associated KPI) is determined by the original (e.g., out-of-the-box or factory) version of the KPI object or by a customized KPI object (or a customized delta KPI object).

[0110] INSERT behavior According to one embodiment, for INSERT operations, if it is a pure custom object, it only needs to be inserted into the custom table. For customized factory objects, the delta needs to be calculated first and only the delta needs to be stored in the custom table with the same KPI id (with the appropriate layer id). Inserts are not made to the base table except during import at provisioning time.

[0111] UPDATE operation According to one embodiment, for UPDATE operations, no updates are made to the base table. If it is a pure custom object, the new metadata can simply be updated in the custom table. If it is a factory object, the delta needs to be calculated and updated (at the appropriate layer) in the custom table.

[0112] DELETE operation According to one embodiment, for a DELETE operation, no deletion is made to the base table. If it is a pure custom object, the new metadata may simply be deleted in the custom table if the ACL allows it. If it is a factory object, the delta record in the custom table may be deleted (thus reverting back to the factory version of the object).

[0113] KPI customization error detection According to one embodiment, the system supports error checking related to errors introduced during the creation of customized KPIs. For example, if a customer creates a customized KPI that adversely affects the operation of a factory KPI, the system may flag an error message to the user to inform them of the event.

[0114] KPI implementation example According to one embodiment, Table 1 shows various examples associated with KPI implementations.

[0115] [Table 4]

[0116] KPI customization usage example According to one embodiment, Table 2 shows various examples of KPI customization use cases.

[0117] [Table 5-1]

[0118] [Table 5-2]

[0119] FIG. 11 illustrates a process for providing KPI customization in an analytical application environment, according to one embodiment.

[0120] As shown in FIG. 11 , according to one embodiment, in step 312, a computer system having computer hardware (e.g., processor, memory) provides access to a database or data warehouse via an analytical application environment adapted to provide data analytics in response to a request.

[0121] In step 314, the semantic layer enables semantic extensions to extend the semantic data model (semantic model) for use in providing data analytics as custom content in the presentation layer.

[0122] In step 316, customization to the key performance indicators (KPIs) is provided by layering variations of the KPI information about the original KPI object, which collectively results in a customized KPI object.

[0123] At run time, in step 318, the system retrieves data from a database or data warehouse and merges layers associated with customized KPIs for use in providing the data as custom content to the presentation layer.

[0124] User interface for customizing KPIs According to one embodiment, the system supports a user interface with icons that describe the 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, the icon changes to visually indicate that the user has modified the KPI. The customized KPI can be used within a KPI deck, card, dashboard, or other type of visualization while retaining its lineage to the original KPI object.

[0125] According to an embodiment, at any stage, the user can revert back to the available or factory KPIs without their pre-configuration. The lineage of the customized KPI to the original KPI also allows it to be patched or otherwise updated when the original KPI is updated.

[0126] For example, as described above, according to one embodiment, the customized KPIs may be stored in a JSON format, such as the example shown below, which may then be used to render a visualization of the KPIs in a user interface.

[0127] According to an embodiment, the JSON information may then be used to provide the information returned by the database to a user interface. The JSON may also indicate, for example, when the data associated with a particular KPI is provided by the original (e.g., out-of-the-box or factory) version of the KPI object or by a customized KPI object.

[0128] According to one embodiment, such information may then be analyzed by the presentation layer or user interface when rendering an indication of the KPI (e.g., including its icon as displayed in the user interface) to indicate whether the icon (and its associated KPI) is determined by the original (e.g., out-of-the-box or factory) version of the KPI object or by a customized KPI object (or a customized delta KPI object).

[0129] 12-21 show various examples of user interfaces that allow users to create and use customized KPIs, according to one embodiment.

[0130] As shown in FIGS. 12-13, user interface 330 allows a user to view and select various analysis decks to use or customize, each of which may include one or more KPIs that display values ​​or other information within the deck.

[0131] An array of KPIs can be viewed and specific KPIs can be selected for customization, as shown in Figure 14. Different icons can be provided to indicate which KPIs are provided out-of-the-box or factory-provided; and which KPIs have been customized to suit a particular, e.g., customer site, department, or user.

[0132] For example, as shown in FIG. 14, the “Sales” KPI is associated with a particular icon that indicates in this example that the associated KPI is an original (e.g., out-of-the-box or factory) KPI.

[0133] Depending on the particular implementation, different approaches may be used to provide a distinction between the icon associated with the original version of the KPI object and the icon associated with the customized KPI object, including, for example, different types of icon colors and / or different indicia or other design or decorative features.

[0134] As shown in Figures 15-18, KPI attributes may be viewed or modified and changes may be saved. For example, as described above, according to one embodiment, when a user creates a new KPI object or customizes the original (e.g., out-of-the-box or factory) version of a KPI object, the system saves this addition / customization in a custom table.

[0135] When a KPI is customized, the system changes its icon to indicate that it is now a customized KPI, as shown in Figure 19. However, as described above, the use of a layered customization data model allows the customized KPI to retain its lineage to the original, e.g., out-of-the-box or factory-provided KPI, and thus improvements, updates, patches, or other modifications to the out-of-the-box or factory-provided KPI may also be surfaced within the customized KPI.

[0136] For example, as shown in Figure 19, the "Sales" KPI has been modified by the user to become the "My Sales Revenue" KPI, and in this example is associated with a specific icon indicating that the associated KPI is a customized KPI. In this particular example, the system also reorganizes the KPIs according to the date they were modified.

[0137] As shown in FIG. 20, at a later point in time, the user may choose to revert the customized KPI back to its original, e.g., out-of-the-box or factory-provided, KPI.

[0138] When reverting to its original configuration, the icon associated with that KPI may likewise revert back to its original icon, as shown in Figure 21. For example, the "My Sales Revenue" KPI may be reverted back to the "Sales" KPI, and its associated icon may be reverted back to indicate that its associated KPI is again the original (e.g., available out-of-the-box or factory) KPI icon, as first shown in Figure 14.

[0139] FIG. 22 illustrates a process for providing KPI customization in an analytical application environment, according to one embodiment.

[0140] As shown in FIG. 22, according to one embodiment, in step 342, a computer system having computer hardware (e.g., processor, memory) provides access to a database or data warehouse via an analytical application environment adapted to provide data analytics in response to a request.

[0141] In step 344, the semantic layer enables semantic extensions to extend the semantic data model (semantic model) for use in providing data analytics as custom content in the presentation layer; where customization to key performance indicators (KPIs) can be provided by layering variations of KPI information about the original KPI object, which collectively results in a customized KPI object; at run time, the layers associated with the customized KPI are merged for use in retrieving data from a database or data warehouse and providing the data to the presentation layer as custom content.

[0142] In step 346, icons describing the original KPI and the KPIs modified by the user are provided in the user interface; where, when the user modifies the original KPI object to create a customized KPI or KPI card, the icon is changed to visually indicate that the user has modified the KPI.

[0143] In step 348, the system enables the user to use the customized KPI within their KPI deck, card, dashboard, or other type of visualization; while the customized KPI itself retains its lineage to the original KPI object.

[0144] According to various embodiments, aspects of the present disclosure are set forth in the following numbered clauses: 1. A system for providing key performance indicator (KPI) customization in an analytical application environment, comprising: a computer including one or more processors that provides access to an analytical application environment; The system allows for customization of key performance indicators derived from multiple layers, which allows for upgrades and reversion of changes in key performance indicators while providing customized key performance indicators based on the original version as a whole; The customizations are applied at run time when the original key performance indicator definition and one or more extensions are merged.

[0145] 2. The system of clause 1, wherein data is accessed through a base table containing key performance indicator objects provided as read-only copies, and when a user creates a new key performance indicator object or customizes the original version of the key performance indicator object, the system stores customization instructions in a custom table.

[0146] 3. The system of clause 1, wherein the key performance indicator model may be used in connection with a presentation layer of the data analytics environment to prepare user interface decks, cards, dashboards, or other visualizations associated with customer data and maintained within the data analytics environment.

[0147] 4. The system of clause 1, wherein the customized key performance indicators are stored in JSON format and used to render a visualization of the key performance indicators in a user interface.

[0148] 5. The system of clause 1, wherein the system is provided in a cloud or multi-tenant environment, wherein a first tenant may make a first set of changes to an original version of a key performance indicator object, the first set of changes being stored as a first delta-KPI1, and a second tenant may make a second set of changes to the original version of the key performance indicator object, the second set of changes being stored as a second delta-KPI.

[0149] 6. A method for providing key performance indicator (KPI) customization in an analytical application environment, comprising: a computer including one or more processors providing access to an analytical application environment; providing customization of key performance indicators derived from multiple layers, which, in its entirety, provides customized key performance indicators based on the original version while allowing for upgrades and reversion of changes in the key performance indicators; The customizations are applied at run time when the original key performance indicator definition and one or more extensions are merged.

[0150] 7. The method of clause 6, wherein data is accessed through a base table containing key performance indicator objects provided as read-only copies, and when a user creates a new key performance indicator object or customizes the original version of the key performance indicator object, the system stores customization instructions in a custom table.

[0151] 8. The method described in clause 6, wherein the key performance indicator model may be used in connection with a presentation layer of the data analytics environment to prepare user interface decks, cards, dashboards, or other visualizations associated with Customer Data and maintained within the data analytics environment.

[0152] 9. The method of clause 6, wherein the customized key performance indicators are stored in JSON format and used to render a visualization of the key performance indicators in a user interface.

[0153] 10. The method of clause 6, wherein the system is provided in a cloud or multi-tenant environment, wherein a first tenant may make a first set of changes to an original version of a key performance indicator object, the first set of changes being stored as a first delta-KPI, and a second tenant may make a second set of changes to the original version of the key performance indicator object, the second set of changes being stored as a second delta-KPI.

[0154] 11. A non-transitory computer-readable storage medium having instructions that, when read and executed by a computer including one or more processors, cause the computer to perform a method, the method comprising: Providing access to an analytical application environment; and providing customization of key performance indicators derived from multiple layers, which, in its entirety, provides customized key performance indicators based on the original version while allowing for upgrades and reversion of changes in the key performance indicators; The customizations are applied at run time when the original key performance indicator definition and one or more extensions are merged.

[0155] 12. The non-transitory computer-readable storage medium of clause 11, wherein the data is accessed through a base table containing key performance indicator objects provided as read-only copies, and when a user creates a new key performance indicator object or customizes an original version of a key performance indicator object, the system stores customization instructions in a custom table.

[0156] 13. The non-transitory computer-readable storage medium of clause 11, wherein the key performance indicator model may be used in connection with a presentation layer of the data analytics environment to prepare user interface decks, cards, dashboards, or other visualizations associated with Customer Data and maintained within the data analytics environment.

[0157] 14. The non-transitory computer-readable storage medium of clause 11, wherein the customized key performance indicators are stored in JSON format and used to render a visualization of the key performance indicators in a user interface.

[0158] 15. The non-transitory computer-readable storage medium of clause 11, wherein the system is provided in a cloud or multi-tenant environment, wherein a first tenant may make a first set of changes to an original version of a key performance indicator object, the first set of changes being stored as a first delta-KPI1, and a second tenant may make a second set of changes to the original version of the key performance indicator object, the second set of changes being stored as a second delta-KPI.

[0159] 16. A system for providing key performance indicator (KPI) customization in an analytical application environment, comprising a user interface for modification of key performance indicator objects; a computer including one or more processors that provides access to an analytical application environment; The system allows for customization of key performance indicators derived from multiple layers that collectively provide customized key performance indicators based on the original versions, the customizations being applied at runtime when the original key performance indicator definitions and one or more extensions are merged; The system is adapted to provide icons in a user interface that describe the original and user-modified key performance indicators, and when a user modifies an original key performance indicator object to create a customized key performance indicator, the icon changes to visually indicate that the user has modified the key performance indicator.

[0160] 17. The system of clause 16, wherein the key performance indicator model may be used in connection with a presentation layer of the data analytics environment to prepare user interface decks, cards, dashboards, or other visualizations associated with customer data and maintained within the data analytics environment.

[0161] 18. The system in clause 16 is provided in a cloud or multi-tenant environment.

[0162] 19. The system of clause 16, wherein the customized key performance indicators are stored in JSON format, the JSON format is used to provide information returned by the database to the user interface and to indicate when data associated with a particular key performance indicator is provided by the original version of the key performance indicator object or by the customized key performance indicator object, the information being parsed by the presentation layer or user interface when rendering an indication of the key performance indicator, including its icon displayed in the user interface.

[0163] 20. The system described in clause 1, wherein an array of key performance indicators may be viewed from which a particular key performance indicator is selected for customization, and icons are provided to indicate which key performance indicator has been customized, and at a later point in time, the user may choose to revert the customized key performance indicator back to its original key performance indicator, and the icon associated with that key performance indicator will revert to its original icon.

[0164] 21. A method for providing key performance indicator (KPI) customization in an analytical application environment, including a user interface for modification of key performance indicator objects, the method comprising: a computer including one or more processors providing access to an analytical application environment; providing customization of key performance indicators derived from multiple layers that generally provide customized key performance indicators based on the original versions, the customizations being applied at run time when the original key performance indicator definitions and the one or more extensions are merged; The system is adapted to provide icons in a user interface that describe the original and user-modified key performance indicators, and when a user modifies an original key performance indicator object to create a customized key performance indicator, the icon changes to visually indicate that the user has modified the key performance indicator.

[0165] 22. The method of clause 21, wherein the key performance indicator model may be used in connection with a presentation layer of the data analytics environment to prepare user interface decks, cards, dashboards, or other visualizations associated with customer data and maintained within the data analytics environment.

[0166] 23. The method described in clause 21, wherein the system is provided in a cloud or multi-tenant environment.

[0167] 24. The method of clause 21, wherein the customized key performance indicators are stored in JSON format, the JSON format is used to provide information returned by the database to the user interface and to indicate when data associated with a particular key performance indicator is provided by the original version of the key performance indicator object or by the customized key performance indicator object, and the information is parsed by the presentation layer or user interface when rendering an indication of the key performance indicator, including its icon displayed in the user interface.

[0168] 25. The method of clause 21, wherein an array of key performance indicators may be viewed from which a particular key performance indicator is selected for customization, icons are provided to indicate which key performance indicator has been customized, and at a later point in time the user may choose to revert the customized key performance indicator back to its original key performance indicator, and the icon associated with that key performance indicator will revert to its original icon.

[0169] 26. A non-transitory computer-readable storage medium having instructions that, when read and executed by a computer including one or more processors, cause the computer to perform a method, the method comprising: a computer including one or more processors providing access to an analytical application environment; providing customization of key performance indicators derived from multiple layers that generally provide customized key performance indicators based on the original versions, the customizations being applied at run time when the original key performance indicator definitions and the one or more extensions are merged; The system is adapted to provide icons in a user interface that describe the original and user-modified key performance indicators, and when a user modifies an original key performance indicator object to create a customized key performance indicator, the icon changes to visually indicate that the user has modified the key performance indicator.

[0170] 27. The non-transitory computer-readable storage medium of clause 26, wherein the key performance indicator model may be used in connection with a presentation layer of the data analytics environment to prepare user interface decks, cards, dashboards, or other visualizations associated with Customer Data and maintained within the data analytics environment.

[0171] 28. The non-transitory computer-readable storage medium described in clause 26, wherein the system is provided in a cloud or multi-tenant environment.

[0172] 29. The non-transitory computer-readable storage medium of clause 26, wherein the customized key performance indicators are stored in JSON format, the JSON format being used to provide information returned by the database to the user interface and to indicate when data associated with a particular key performance indicator is provided by the original version of the key performance indicator object or by the customized key performance indicator object, the information being parsed by the presentation layer or user interface when rendering an indication of the key performance indicator, including its icon displayed in the user interface.

[0173] 30. The non-transitory computer-readable storage medium of clause 26, wherein an array of key performance indicators may be viewed from which a particular key performance indicator is selected for customization and icons are provided to indicate which key performance indicator has been customized, and at a later point in time, the user may choose to revert the customized key performance indicator back to its original key performance indicator, and the icon associated with that key performance indicator will revert to its original icon.

[0174] According to various embodiments, the teachings herein may be conveniently implemented by one or more conventional general-purpose or special-purpose digital computers, computing devices, machines, or microprocessors, including one or more processors, memory, and / or computer-readable storage media programmed according to the teachings of the present disclosure. A skilled programmer can readily prepare appropriate software coding based on the teachings of the present disclosure, as will be apparent to those skilled in the software arts.

[0175] In some embodiments, the present invention includes a computer program product that is a non-transitory computer-readable storage medium(s) having instructions stored thereon. The computer program product can be used to program a computer to perform any of the processes of the present teachings. For example, such a storage medium may include, but is not limited to, a hard disk drive, a hard disk, a fixed disk, or other electromechanical data storage device, a floppy disk, an optical disk, a DVD, a CD-ROM, a microdrive, and any type of disk, including a magneto-optical disk, a ROM, a RAM, an EPROM, an EEPROM, a DRAM, a VRAM, a flash memory device, a magnetic or optical card, a nanosystem, or any other type of storage medium or device suitable for temporarily storing instructions and / or data.

[0176] The above description has been provided for purposes of illustration and description. It is not intended to be exhaustive or to limit the scope of protection to the precise form disclosed. Many modifications and variations will be apparent to those skilled in the art.

[0177] For example, although some of the examples provided herein illustrate operation of an analytics application environment with an enterprise software application / data environment, such as, for example, an Oracle Fusion Applications environment, or within the context of a Software-As-A-Service (SaaS) or cloud environment, such as, for example, an Oracle Analytics Cloud or Oracle Cloud Infrastructure environment, according to various embodiments, the systems and methods described herein may be used with other types of enterprise software application / data environments, cloud environments, cloud services, cloud computing, or other computing environments.

[0178] The embodiments have been chosen and described to best explain the principles of the present teachings and their practical application, thereby enabling those skilled in the art to appreciate various embodiments and, in addition, various modifications thereof suited to particular uses contemplated. The scope of the present disclosure is indicated by the appended claims and their equivalents.< / metadata>

Claims

1. 1. A system for providing key performance indicator (KPI) customization in an analytical application environment, comprising: a computer including one or more processors and memory that provides access to an analytical application environment; the memory stores a base table including key performance indicator objects provided as read-only copies; the one or more processors enable customization of key performance indicators derived from multiple layers, and maintain a lineage in the customized key performance indicators to revert to original pre-customization versions of the key performance indicators, the multiple layers collectively providing customized key performance indicators based on original versions while the lineage enables upgrades and reversion of changes in the key performance indicators; the one or more processors accept input of metrics to be added to the original key performance indicator definition at run time for the customization; the one or more processors generate a customized key performance indicator object by merging the original key performance indicator definition with the added indicator; The one or more processors store the customization content in a custom table.

2. The customization is: inserting data into the custom table; updating the data in the custom table; and deleting data from the custom table.

3. 3. The system of claim 1 or 2, wherein the key performance indicator model is used in connection with a presentation layer of a data analytics environment to prepare user interface decks, cards, dashboards, or other visualizations associated with customer data and maintained within the data analytics environment.

4. The system of any of claims 1 to 3, wherein the customized key performance indicators are stored in JSON format and used to render a visualization of said key performance indicators in a user interface.

5. 5. The system of claim 1, wherein the system is provided in a cloud or multi-tenant environment, wherein a first tenant can make a first set of changes to an original version of a key performance indicator object, the first set of changes being stored as a first delta-KPI, and a second tenant can make a second set of changes to the original version of the key performance indicator object, the second set of changes being stored as a second delta-KPI.

6. 1. A method for providing key performance indicator (KPI) customization in an analytical application environment, comprising: a computer including one or more processors providing access to an analytical application environment; loading into memory a base table containing key performance indicator objects provided as read-only copies; providing a screen that accepts customization of key performance indicators derived from multiple layers; the one or more processors accepting input of metrics to be added to the original key performance indicator definition at run time for the customization; generating, by the one or more processors, a customized key performance indicator object by merging the original key performance indicator definition with the added indicator; causing the one or more processors to maintain a lineage in the customized key performance indicators back to the original pre-customization version of the key performance indicators; the one or more processors storing the customization in a custom table; The method wherein the layers collectively provide customized key performance indicators based on original versions, while the lineage allows for upgrades and reversion of changes in the key performance indicators.

7. The customization comprises: an operation of inserting data into the custom table; updating the data in the custom table; and deleting the data in the custom table.

8. 8. The method of claim 6 or 7, wherein the key performance indicator model is used in connection with a presentation layer of a data analytics environment to prepare user interface decks, cards, dashboards, or other visualizations associated with customer data and maintained within the data analytics environment.

9. The method according to any of claims 6 to 8, wherein the customized key performance indicators are stored in JSON format and used to render a visualization of said key performance indicators in a user interface.

10. The method of any of claims 6 to 9, wherein the method is provided in a cloud or multi-tenant environment, wherein a first tenant can make a first set of changes to an original version of a key performance indicator object, the first set of changes being stored as a first delta-KPI, and a second tenant can make a second set of changes to the original version of the key performance indicator object, the second set of changes being stored as a second delta-KPI.

11. A computer program for causing a computer to execute the method according to any one of claims 6 to 10.

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