System and method for providing a user interface for KPI customization in an analytics application environment

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 type of cloud or computing environment. 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 supports a user interface with icons describing the original (e.g., available out-of-the-box or factory) KPI and user-modified KPIs. When a user modifies the 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 in a KPI deck, card, dashboard, or other type of visualization, while retaining lineage to the original KPI object.

Description

Technical Field

[0001] Copyright Notice Part of the disclosure of this patent document contains materials that are subject to copyright protection. Since the patent document or patent disclosure is publicly available in the patent files and records of the United States Patent and Trademark Office, the copyright owner has no objection to its reproduction by anyone, but in the event that this is not the case, the copyright owner retains all copyrights without exception.

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

[0003] Technical Field: The embodiments described herein generally relate 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 analytical application environments. [Background technology]

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

[0005] There is growing interest in developing software applications that leverage data analytics in conjunction with an organization's enterprise software application / data environment (e.g., an Oracle Fusion Applications environment or other types of enterprise software application / data environments) or in conjunction with a SaaS (Software-As-A-Service) or cloud environment (e.g., an Oracle Analytics Cloud or Oracle Cloud Infrastructure environment, or other types of computing cloud environments). [Overview of the project] [Problems that the invention aims to solve]

[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 purpose of providing such KPIs or other business intelligence data. [Means for solving the problem]

[0007] overview: In one embodiment, the system and method described herein provide for providing key performance indicator (KPI) customization in an analytical application environment, enabling 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 as a whole supports customization derived from multiple layers, which can result in customized performance metrics or KPI objects.

[0008] In one embodiment, the system enables the creation of customized KPIs by hierarchically layering variations of KPI information about an original (e.g., readily available or factory) KPI object, which are merged at runtime to create the final customized KPI. Each delta-KPI itself may also support multiple levels, e.g., site / user level / layer. This technique 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] In one embodiment, the system supports a user interface with icons describing original (e.g., available without pre-configuration 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 visually indicate that the user has modified the KPI. Customized KPIs can be used within KPI decks, cards, dashboards, or other types of visualizations while maintaining their lineage to the original KPI object. [Brief explanation of the drawing]

[0010] [Figure 1] This document describes a system for providing an analytical application environment according to one embodiment. [Figure 2] This document presents a system, according to one embodiment, that supports scalability and customization in an analytical application environment. [Figure 3] This demonstrates how this system can be used to provide KPI customization according to one embodiment. [Figure 4] This document illustrates an example of KPI customization using one embodiment. [Figure 5] This figure shows exemplary metadata according to one embodiment. [Figure 6] Further examples of KPI customization by one embodiment are shown. [Figure 7] This figure shows another exemplary metadata according to one embodiment. [Figure 8] Further examples of KPI customization by one embodiment are shown. [Figure 9] This figure shows an exemplary set of operations for retrieving data associated with a KPI, according to one embodiment. [Figure 10] This figure shows an exemplary merged JSON file according to one embodiment. [Figure 11] This document describes a process for providing KPI customization in an analytics application environment according to one embodiment. [Figure 12] This figure shows an exemplary user interface that, according to one embodiment, allows a user to create and use customized KPIs. [Figure 13] This figure shows an exemplary user interface that, according to one embodiment, allows a user to create and use customized KPIs. [Figure 14] This figure shows an exemplary user interface that, according to one embodiment, allows a user to create and use customized KPIs. [Figure 15] FIG. is an exemplary user interface that enables a user to create and use customized KPIs according to an embodiment. [Figure 16] FIG. is an exemplary user interface that enables a user to create and use customized KPIs according to an embodiment. [Figure 17] FIG. is an exemplary user interface that enables a user to create and use customized KPIs according to an embodiment. [Figure 18] FIG. is an exemplary user interface that enables a user to create and use customized KPIs according to an embodiment. [Figure 19] FIG. is an exemplary user interface that enables a user to create and use customized KPIs according to an embodiment. [Figure 20] FIG. is an exemplary user interface that enables a user to create and use customized KPIs according to an embodiment. [Figure 21] FIG. is an exemplary user interface that enables a user to create and use customized KPIs according to an embodiment. [Figure 22] FIG. is a diagram showing a process for providing KPI customization in an analysis application environment according to an embodiment.

MODE FOR CARRYING OUT THE INVENTION

[0011] Detailed description: As described above, within an organization, computer-based investigations or analyses of data are enabled by data analytics to derive conclusions or other information from large amounts of data, and information describing corporate data in a form that enables strategic business decisions to be made by business intelligence tools is provided to business users of the organization.

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

[0013] According to one embodiment, what is described herein is a system and method for providing key performance indicator (KPI) customization in an analytics 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 as a whole supports customizations derived from multiple layers that can result in customized performance metrics or KPI objects.

[0014] According to one embodiment, the system enables the creation of customized KPIs by hierarchically varying KPI information about the original (e.g., factory, available without pre-configuration) KPI objects that are merged at runtime to create the final customized KPI. Each delta-KPI itself can also support multiple, for example, site / user level / layers. This approach can be used to provide scalability for user interface decks / dashboards where KPI visualization objects such as decks, cards, dashboards, or other types of visualizations appear.

[0015] According to one embodiment, the system as a whole supports customizations derived from multiple layers that may result in customized performance metrics or KPI objects that do not modify the base version or original (e.g., available without prior configuration or factory) version of the KPI object, and allows for upgrading, reverting, and tracking changes in the KPI editor or user interface.

[0016] In one embodiment, a customer may move data, create key performance indicators (KPIs), and present them as decks, cards, dashboards, or other types of visualizations. Occasionally, a customer may want to customize and extend those KPIs for use in their specific operations, which traditionally requires a "save as" technique to create new KPIs, but would lose the lineage back to the original KPI. By layering variations of KPI information on top of the original (e.g., readily available or factory) KPI object, this feature is particularly useful, for example, in a multi-tenant environment, where a tenant may layer changes to a base KPI plus tenant-specific or user-specific delta KPIs, which are then merged at runtime to create the final customized KPI.

[0017] In one embodiment, the system supports a user interface with icons describing original (e.g., available without pre-configuration 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 visually indicate that the user has modified the KPI. Customized KPIs can be used within KPI decks, cards, dashboards, or other types of visualizations while maintaining their lineage to the original KPI object.

[0018] According to one embodiment, at any stage, the user can revert to the available or factory KPIs without their prior configuration. The lineage of customized KPIs to the original KPIs also allows them to be patched or updated in a different way when the original KPIs are updated.

[0019] Depending on the various embodiments, the technical advantages of the described method include, for example, (1) optimization of storage required for creating and using KPIs, as they are often available without prior configuration or require only moderate tweaks to factory KPI objects, and (2) supportability and ease of upgrading of the underlying factory KPI definitions across subsequent releases.

[0020] Analytics application environment According to the embodiment, for example, a data warehouse environment or component such as ADW (Oracle Autonomous Data Warehouse), ADWC (Oracle Autonomous Data Warehouse Cloud), or other types of data warehouse environments or components designed 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 one embodiment, the 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 different sources. An organization can 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 that organization.

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

[0023] Vertical business applications generally have a narrower scope than horizontal business applications, but they provide access to a defined range of data within a specific area or industry. Examples of vertical business applications include healthcare software or banking software for use within a particular organization.

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

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

[0026] For example, according to one embodiment, the analytics application environment can be used to pre-add relevant metadata describing business-related data objects associated with various business productivity software applications to the reporting interface of a data warehouse instance, such as predefined dashboards, key performance indicators (KPIs), or other types of reports.

[0027] In one embodiment, an analytics application environment may be provided in relation to an analytics cloud environment (analytics cloud), such as an Oracle Analytics Cloud (OAC) environment. Such an environment provides a scalable and secure public cloud service that offers the ability to explore and perform collaborative analytics.

[0028] Figure 1 shows a system for providing an analytical application environment according to one embodiment.

[0029] The example shown and described in Figure 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 capabilities described herein may be used in conjunction with other types of data analytics environments.

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

[0031] According to the embodiments, the components and processes shown in Figure 1 and further described in relation to various other embodiments can be provided as software or program code executable by a computer system or other type of processing device. For example, according to the embodiments, the components and processes described herein can be provided by a cloud computing system or other appropriately programmed computer system.

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

[0033] According to the embodiment, the console interface can 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 SaaS or cloud environment provider and its customers (tenants). For example, according to the embodiment, the console interface can provide an interface that allows customers to provision services for use within their SaaS environment, and an interface that allows customers to configure those provisioned services.

[0034] According to the embodiment, a customer (tenant) can request the provisioning of a customer schema 164 within a data warehouse. The customer can also supply several 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). Subsequently, the provisioning component can provision the requested data warehouse instance containing the customer schema of the data warehouse and add the appropriate information supplied by the customer to the data warehouse instance.

[0035] Furthermore, according to the embodiment, the provisioning component can be used to update or edit data warehouse instances and / or ETL processes operating in the data plane, for example, by changing or updating the frequency of requests for ETL process execution for a specific customer (tenant).

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

[0037] According to the 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 business productivity software applications provisioned in a customer's (tenant's) SaaS environment. The data pipeline / processing may include various functions for extracting transactional data from business applications and databases provisioned in the SaaS environment and then loading the transformed data into a data warehouse.

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

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

[0040] According to the embodiment, the data plane is responsible for performing ETL (Extract, Transform, Load) operations. ETL operations include extracting transactional data from an organization's enterprise software application / data environment, such as business productivity software applications and corresponding transactional databases provided in a SaaS environment; converting the extracted data into a model format; and loading the transformed data into a customer schema in the data warehouse.

[0041] For example, according to one embodiment, each customer (tenant) in 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 be provided with read-only access to the analytical application schema. The analytical application schema may be updated periodically or by other criteria through a data pipeline / process, such as an ETL process.

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

[0043] According to the embodiment, the extraction process 108 can extract transaction data, and once extracted, the data pipeline / process can insert the extracted data into the data staging area. The data staging area can function as a temporary staging area for the extracted data. The integrity of the extracted data can be ensured using data quality components and data protection components. For example, according to the embodiment, the data quality component can verify the data while the extracted data is temporarily held in the data staging area.

[0044] According to the 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 the customer schema of the data warehouse.

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

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

[0047] According to the embodiment, after the extracted data has been transformed, the data pipeline / processing can execute the warehouse load procedure 150 to load the transformed data into the customer schema instance of the data warehouse. Following the step of loading the transformed data into the customer schema, the transformed data can be parsed and used in various additional business intelligence processes.

[0048] According to one embodiment, an exemplary example of an analytical application environment that can utilize the various systems, methods, and features described herein is shown in a U.S. Patent Application titled "SYSTEM AND METHOD FOR CUSTOMIZATION IN AN ANALYTIC APPLICATIONS ENVIRONMENT," filed on 6 May 2020, application number 16 / 868,081, and published under U.S. Patent Application Publication number 20200356575, which is incorporated herein by reference. According to various embodiments, the systems and methods described herein may be used in conjunction with other types of enterprise software applications or data environments, cloud environments, cloud services, cloud computing, or other analytical application or computing environments.

[0049] Scalability and customization Different customers in a data analytics environment will have different requirements regarding how to classify, aggregate, or transform data for the purpose of providing data analytics or business intelligence data, or for developing software analytics applications.

[0050] In one embodiment, to support such different requirements, the system may include a semantic layer that allows the semantic data model (semantic model) to be extended using custom semantic extensions to provide custom content in the presentation layer. An extension wizard or development environment can guide the 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 the production environment.

[0051] Figure 2 shows a system for supporting scalability 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 customer data, which is useful in helping users understand and access that data using commonly understood business terminology.

[0053] As shown in Figure 2, according to one embodiment, the semantic layer 230 may include a packaged (out-of-the-box, ready-to-use, initial) semantic model 232 that can be used to provide packaged content. For example, the system can load data from a customer's enterprise software application or data environment into a data warehouse instance using the ETL or other data pipeline or process described above, 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, which can be used to extend the packaged semantic model to provide custom content to the presentation layer 240.

[0055] In one embodiment, the presentation layer can enable access to data content using, for example, software analytics applications, user interfaces, dashboards, key performance indicators (KPIs), 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, according to one embodiment, as described below, a customized KPI may be created by combining or merging various levels of extensions, including the original, factory, or readily available KPI definitions 302 and customer extensions 304, to produce the resulting or customized KPI card 306.

[0057] According to one embodiment, in addition to the data supplied from the customer's environment using the above-described ETL or other data pipelines or processes, customer data can be loaded into a data warehouse instance using various data models or scenarios that provide opportunities for further scalability and customization.

[0058] Hierarchical KPI Customization According to one embodiment, the system as a whole supports customizations derived from multiple layers that may result in customized performance metrics or KPI objects that do not modify the base version or original (e.g., available without prior configuration or factory) version of the KPI object, and allows for upgrading, reverting, and tracking changes in the KPI editor or user interface.

[0059] In one embodiment, a customer may move data, create key performance indicators (KPIs), and present them as decks, cards, dashboards, or other types of visualizations. Occasionally, a customer may want to customize and extend those KPIs for use in their specific operations, which traditionally requires a "save as" technique to create new KPIs, but would lose the lineage back to the original KPI. By layering variations of KPI information on top of the original (e.g., readily available or factory) KPI object, this feature is particularly useful, for example, in a multi-tenant environment, where a tenant may layer changes to a base KPI plus tenant-specific or user-specific delta KPIs, which are then merged at runtime to create the final customized KPI.

[0060] Figure 3 illustrates how the system can be used to provide KPI customization through one embodiment in which KPI definitions can be extended and merged to provide customized KPIs.

[0061] As described above, according to one embodiment, in an analytics application environment, the presentation layer may enable access to data content using, for example, software analytics applications, user interfaces, dashboards, key performance indicators (KPIs); or other types of reporting or interfaces that 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, for example, provided by Oracle experts as part of Fusion Applications or as Fusion Applications Warehouse (FAW).

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

[0063] Hierarchical Customization Data Model According to one embodiment, the system provides separation at the data model level between the original (e.g., readily available or factory) version of a KPI object and a customized KPI object.

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

[0065] In one embodiment, customer data may be accessed through a base table containing KPI objects that are shipped (i.e., from the factory or system provider) in a state where they are available without prior configuration. A read-only copy of this table may be provided, and there may be no insertions, updates, or deletions to this table by application code. These KPI objects developed in the factory are imported into this table, for example, during system (pod) provisioning. Since the base table is not striped by tenants, there is only one copy of the factory metadata for the entire system (pod), and the table is not duplicated per tenant.

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

[0067] For example, in a multi-tenant analytics application environment, the first tenant may create a first set of changes to the KPI object that are available without prior configuration or to the factory version, and this first set of changes is stored as the first delta KPI. The second tenant may create a different / second set of changes to the KPI object that are available without prior configuration or to the factory version, and this second set of changes is stored as a different / second delta KPI.

[0068] In one embodiment, the system neither modifies the original (e.g., readily available or factory) version of a KPI object nor copies that object to the tenant's stored data space, because doing so would be redundant and would limit the system's ability to link customized KPIs back to the original readily available or factory KPI objects based on delta KPIs.

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

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

[0071] In one embodiment, each KPI may be associated with an ID that identifies the specific KPI, a namespace, metadata, and an access control list (ACL) ID.

[0072] For example, an ID may be provided as a numerical value, and a namespace may indicate the source of a KPI object or delta KPI object. Metadata may define various dimensions, expressions, or other information associated with customer data that will be queried to provide the resulting KPI visualization, as shown in, for example, Exemplary Metadata 1 below. An ACL ID may be used to provide security instructions necessary to access the KPI.

[0073] Example explanation of a KPI customization scenario According to one embodiment, various examples of different KPI customization scenarios are shown below.

[0074] Figure 4 illustrates an exemplary KPI customization by one embodiment in which KPI definitions can be extended and merged to provide customized KPIs. As shown in Figure 4 and partially reproduced below, in this example, the original (e.g., available without pre-configuration or factory) version of the KPI object is not customized:

[0075] [Table 1]

[0076] In this example, as mentioned above, you can access customer data using a version of the KPI object that is available without prior configuration or a factory version, and then generate KPI decks, cards, dashboards, or other types of visualizations based on that data.

[0077] Figure 5 shows exemplary metadata in one embodiment, illustrating the KPI definition associated with a version of a KPI object that is available without prior configuration or a factory version. As shown in Figure 5 and reproduced below, in this example, the KPI provides workforce information, including country location and region, for use when generating the KPI.

[0078]

number

[0079] In this example, metadata can 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 not the city dimension in this example).

[0080] KPI Customization - Adding a New Dimension Figure 6 further illustrates an exemplary KPI customization by one embodiment in which KPI definitions can be extended and merged to provide customized KPIs. As shown in Figure 6 and partially reproduced below, in this example, an available version or factory version of the KPI object is customized, for example, by adding a new dimension to the KPI:

[0081] [Table 2]

[0082] In this example, the modification to the original (e.g., available without prior configuration or factory) version of the KPI object, i.e., the delta-KPI, is:<delta metadata> This includes, as well as, layer IDs and stripe IDs that may be used to support hierarchical KPI customization and customizations 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 embodiment, 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 level customizations.

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

[0085] According to one embodiment, a stripe ID can be used to identify a tenant, for example, in a cloud or multi-tenant environment. This allows a specific 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 differently from the one associated with the base KPI, which would allow, for example, different departments to use different ACLs, and the KPI would be returned appropriately depending on the ACL attributes of the department or user accessing that customized KPI.

[0087] Figure 7 shows another exemplary metadata in one embodiment, illustrating the KPI definition associated with a version or factory version of a KPI object that is available without prior configuration.

[0088] As illustrated in Figure 7 and reproduced below, this embodiment uses a delta KPI definition that is available without prior configuration of the KPI object or associated with a factory version, in which the user adds a dimension about city. The KPI will be effectively customized and therefore, using the combined (KPI + delta-KPI) metadata, it may be possible to access customer data and generate a data-based KPI deck, card, dashboard, or other type of visualization that includes information based on the country, region, and / or city dimensions added by the delta-KPI customization in this example.

[0089]

number

[0090] In this example, the original KPI metadata, which is available without prior configuration of the KPI object or provided by a factory version and is directed to a country or region, is not repeated in the Delta KPI metadata. However, when a query is made against 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 in order to process the query.

[0091] Since the original, pre-configured, or factory versions of KPI objects are not modified, if, for example, Oracle makes any changes to the original KPI, the original KPI will continue to function, and the delta KPIs will also continue to function as long as they do not conflict with the underlying factory KPIs, and in addition, they will benefit from the original KPI being updated, patched, or otherwise modified.

[0092] KPI Customization - Creating New Customized KPIs Figure 8 further illustrates an exemplary KPI customization by one embodiment in which KPI definitions can be extended and merged to provide customized KPIs. As shown in Figure 8 and partially reproduced below, in this example, a new customized KPI is created, which is optional and not necessarily a starting point, but can be an available version or factory version of the KPI object without any prior configuration.

[0093] [Table 3]

[0094] In this example demonstrating a new customized KPI, the customer did not create delta KPI metadata when creating the new KPI, but instead created the new KPI (in this example, in the namespace "Admin"). In this example, KPI ID=3 indicates that the KPI is a new customized KPI and not a delta KPI. In addition, in this example, <metadata>The layer is null in this instance because, in this case too, it is not a delta KPI but a new KPI customization (optionally starting with a version available without prior configuration of the KPI object or a factory version).

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

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

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

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

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

[0100] In other embodiments, the system may access data not through a semantic model or semantic layer, but, for example, by directly accessing the data itself, or through some other model or layer, or through some other intermediate component that provides access to customer data and supports data retrieval according to KPI objects and / or customized KPI objects.

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

[0102] READ operation In one embodiment, a READ operation may retrieve data associated with a KPI from the database using pseudo-SQL logic or other data retrieval processes. In the following example, the table includes factory KPIs (not customized by the tenant, as in 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] Figure 9 shows an exemplary set of operations for retrieving data associated with a KPI according to one embodiment. In this example, as shown in Figure 9 and reproduced below,

[0104]

number

[0105] Figure 10 shows an exemplary merged JSON file in one embodiment, including additional properties at each KPI attribute level to indicate which attributes are customized attributes compared to those provided by the factory. In this example, as illustrated in Figure 10 and reproduced below,

[0106]

number

[0107] According to one embodiment, the data returned from the database using the above process needs to be further processed before being provided to the presentation layer or user interface. For example, the KPIs, f_metadata, and c_metadata_site within the "FACTORYCUSTOM" set (310) would be compared, merged, and processed according to a supported customized use case. Using the above example where the factory model includes a country, and then a city delta is added, the JSON would then include all three dimensions—either available without prior configuration of the KPI object or specified by the factory version and the customized delta-KPI object.

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

[0109] According to one embodiment, when rendering the KPI indication (e.g., including its icon as displayed in the user interface), such information may be parsed by the presentation layer or user interface to indicate whether the icon (and its associated KPI) is determined by the original (e.g., readily available 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 an INSERT operation, if it is a purely custom object, it only needs to be inserted into the custom table. For a factory object that is customized, the delta must be calculated first, and only the delta needs to be stored in the custom table (with the appropriate layer ID, and the same KPI ID). Insertions are not performed on the base table except during the import at provisioning time.

[0111] UPDATE operation In one embodiment, an UPDATE operation does not update the base table. If it is a purely custom object, the new metadata can simply be updated within the custom table. If it is a factory object, the delta must be calculated and updated in the custom table (at the appropriate layer).

[0112] DELETE Action In one embodiment, a DELETE operation does not delete anything from the base table. If it is a pure custom object, new metadata may simply be deleted within the custom table if the ACL allows it. If it is a factory object, delta records within the custom table may be deleted (and thus revert to the factory version of the object).

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

[0114] Examples of KPI achievement According to one embodiment, Table 1 shows various examples related to KPI achievement.

[0115] [Table 4]

[0116] KPI Customization Usage Examples According to one embodiment, Table 2 shows various examples of KPI customization use cases.

[0117] [Table 5-1]

[0118] [Table 5-2]

[0119] Figure 11 shows a process for providing KPI customization in an analytics application environment according to one embodiment.

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

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

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

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

[0124] User interface for KPI customization In one embodiment, the system supports a user interface with icons describing original (e.g., available without pre-configuration 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 visually indicate that the user has modified the KPI. Customized KPIs can be used within KPI decks, cards, dashboards, or other types of visualizations while maintaining their lineage to the original KPI object.

[0125] According to one embodiment, at any stage, the user can revert to the available or factory KPIs without their prior configuration. The lineage of customized KPIs to the original KPIs also allows them to be patched or updated in a different way when the original KPIs are updated.

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

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

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

[0129] Figures 12 to 21 show various examples of a user interface that allows a user to create and use customized KPIs according to one embodiment.

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

[0131] As shown in Figure 14, an array of KPIs can be viewed, and specific KPIs can be selected for customization. Different icons may be provided to indicate which KPIs are available and provided without pre-configuration, or which are factory-provided; and which KPIs are customized to suit a specific, e.g., customer site, department, or user.

[0132] For example, as shown in Figure 14, the "Sales" KPI is associated with a specific icon in this example that indicates its associated KPI is the original (e.g., available without pre-configuration or factory) KPI.

[0133] Depending on the specific implementation, different methods may be used to distinguish 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 markings or other design or decorative features.

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

[0135] As shown in Figure 19, when a KPI is customized, the system changes its icon to indicate that it is now a customized KPI. However, as mentioned above, the use of a hierarchical customized data model allows customized KPIs to maintain lineage to the original, for example, the KPI available without pre-configuration or provided at the factory, and therefore improvements, updates, patches, or other modifications to the KPI available without pre-configuration or provided at the factory may also surface 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, the relevant KPI is associated with a specific icon indicating that it is a customized KPI. In this particular example, the system also reorganizes the KPIs according to the modification date.

[0137] As shown in Figure 20, at a later point, the user may choose to revert the customized KPIs back to their original, for example, the KPIs available without prior configuration or provided at the factory.

[0138] As shown in Figure 21, when the configuration is restored to its original state, the icon associated with that KPI may also revert to its original icon. For example, the "My Sales Revenue" KPI may revert to the "Sales" KPI, and its associated icon may revert to indicate that the associated KPI is again the icon of the original (e.g., available without pre-configuration or factory) KPI, as initially shown in Figure 14.

[0139] Figure 22 shows a process for providing KPI customization in an analytics application environment according to one embodiment.

[0140] As shown in Figure 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 analytics application environment adapted to provide data analytics in response to requests.

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

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

[0143] In step 348, the system allows users to use customized KPIs within their own KPI decks, cards, dashboards, or other types of visualizations; while the customized KPIs themselves maintain their lineage to the original KPI objects.

[0144] Depending on the various embodiments, aspects of this disclosure are described in the following numbered clauses. 1. A system for providing customization of key performance indicators (KPIs) in an analytical application environment, A computer with one or more processors that provides access to an analytical application environment, This system allows for the customization of key performance indicators (CPRs) derived from multiple layers, providing, as a whole, customized CPRs based on the original version, while also enabling upgrades and reverting changes to CPRs. Customizations are applied at runtime when the original key performance indicator definition and one or more extensions are merged.

[0145] 2. The system, as described in Clause 1, accesses data through a base table containing key performance indicator (KPI) objects provided as read-only copies, and when a user creates a new KPI object or customizes an original version of a KPI object, the system stores the customization instructions in a custom table.

[0146] 3. The System described in Clause 1, in relation to the presentation layer of the data analytics environment, in order to prepare user interface decks, cards, dashboards, or other visualizations associated with customer data and maintained within the data analytics environment.

[0147] 4. Customized key performance indicators are stored in JSON format and used to render visualizations of key performance indicators in the user interface, as described in Clause 1 of the system.

[0148] 5. The system is provided in a cloud or multi-tenant environment, and the first tenant may create a first set of changes to the original version of the key performance indicator object, the first set of changes being stored as the first Delta-KP1, and the second tenant may create a second set of changes to the original version of the key performance indicator object, the second set of changes being stored as the second Delta-KPI, as described in Clause 1.

[0149] 6. A method for providing customization of key performance indicators (KPIs) in an analytical application environment, A computer containing one or more processors provides access to an analytical application environment, This includes providing customization of key performance indicators (CPIs) derived from multiple layers, which, as a whole, provides customized CPIs based on the original version, while also allowing for upgrades and reverting changes in CPIs. Customizations are applied at runtime when the original key performance indicator definition and one or more extensions are merged.

[0150] 7. If data is accessed by a base table containing key performance indicator objects provided as read-only copies, and a user creates a new key performance indicator object or customizes an original version of a key performance indicator object, the system stores the customization instructions in a custom table, as described in Clause 6.

[0151] 8. The method according to Clause 6, wherein the key performance indicator model may be used in relation to the 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 according to Clause 6, wherein customized key performance indicators are stored in JSON format and used to render visualizations of key performance indicators in the user interface.

[0153] 10. The system is provided in a cloud or multi-tenant environment, and the first tenant may create a first set of changes to the original version of the key performance indicator object, the first set of changes being stored as the first Delta-KP1, and the second tenant may create a second set of changes to the original version of the key performance indicator object, the second set of changes being stored as the second Delta-KPI, as described in Clause 6.

[0154] 11. A non-temporary computer-readable storage medium having instructions, wherein the instructions are read by a computer including one or more processors and, when executed, cause the computer to execute a method, and this method To provide access to the analytical application environment, This includes providing customization of key performance indicators (CPIs) derived from multiple layers, which, as a whole, provides customized CPIs based on the original version, while also allowing for upgrades and reverting changes in CPIs. Customizations are applied at runtime when the original key performance indicator definition and one or more extensions are merged.

[0155] 12. When data is accessed by a base table containing key performance indicator objects provided as read-only copies, and a user creates a new key performance indicator object or customizes an original version of a key performance indicator object, the System stores the customization instructions in a custom table, a non-temporary computer-readable storage medium as described in Clause 11.

[0156] 13. Non-temporary computer-readable storage media as described in Clause 11, which may be used in relation to the 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. Customized key performance indicators are stored in JSON format on a non-temporary computer-readable storage medium as described in Clause 11, which is used to render visualizations of key performance indicators in the user interface.

[0158] 15. The system is provided in a cloud or multi-tenant environment, and the first tenant may create a first set of changes to the original version of the key performance indicator objects, the first set of changes being stored as the first delta-KP1, and the second tenant may create a second set of changes to the original version of the key performance indicator objects, the second set of changes being stored as the second delta-KPI, on a non-temporary computer-readable storage medium as described in Clause 11.

[0159] 16. A system for providing Key Performance Indicator (KPI) customization in an analytical application environment, which includes a user interface for modifying Key Performance Indicator objects. A computer with one or more processors that provides access to an analytical application environment, This system, overall, allows for the customization of key performance indicators (CPRs) derived from multiple layers, providing customized CPRs based on the original version. The customization is applied at runtime when the original CPR definition and one or more extensions are merged. This system is adapted to provide icons in the user interface that describe the original key performance indicators (CPRs) and user-modified CPRs. When a user modifies the original CPR object to create a customized CPR, its icon changes to visually indicate that the user has modified the CPR.

[0160] 17. The System described in Clause 16, in relation to the presentation layer of the data analytics environment, in order to prepare user interface decks, cards, dashboards, or other visualizations associated with customer data and maintained within the data analytics environment.

[0161] 18. This system is provided in a cloud or multi-tenant environment, as defined in Clause 16.

[0162] 19. Customized key performance indicators are stored in JSON format, which is used to provide information returned to the user interface by the database and to indicate when the 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 the indication of the key performance indicator, including its icon displayed in the user interface, as described in Clause 16 of the System.

[0163] 20. The system described in Clause 1, from which a user can view an array of key performance indicators (KPIs), from which a specific KPI can be selected for customization, an icon is provided to indicate which KPI has been customized, and at a later point, the user can choose to revert a customized KPI back to its original KPI, and the icon associated with that KPI reverts to its original icon.

[0164] 21. A method for providing key performance indicator (KPI) customization in an analytical application environment, comprising a user interface for modifying key performance indicator objects, the method includes A computer containing one or more processors provides access to an analytical application environment, Overall, this includes providing customized key performance indicators (CPRs) derived from multiple layers that provide customized CPRs based on the original version, and the customizations are applied at runtime when the original CPR definition and one or more extensions are merged. This system is adapted to provide icons in the user interface that describe the original key performance indicators (CPRs) and user-modified CPRs. When a user modifies the original CPR object to create a customized CPR, its icon changes to visually indicate that the user has modified the CPR.

[0165] 22. The method according to Clause 21, wherein the key performance indicator model may be used in relation to the 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 system is provided in a cloud or multi-tenant environment as described in Clause 21.

[0167] 24. Customized key performance indicators are stored in JSON format, the JSON format is used to provide information returned to the user interface by the database and to indicate when the 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 the indication of the key performance indicator, including its icon displayed in the user interface, as described in Clause 21.

[0168] 25. The method as described in Clause 21, from which a user can view an array of key performance indicators (KPIs), from which a specific KPI can be selected for customization, an icon is provided to indicate which KPI has been customized, and at a later point the user can choose to revert a customized KPI back to its original KPI, and the icon associated with that KPI reverts to its original icon.

[0169] 26. A non-temporary computer-readable storage medium having instructions, wherein the instructions are read by a computer including one or more processors, and when executed, the computer causes the computer to execute a method, and this method A computer containing one or more processors provides access to an analytical application environment, Overall, this includes providing customized key performance indicators (CPRs) derived from multiple layers that provide customized CPRs based on the original version, and the customizations are applied at runtime when the original CPR definition and one or more extensions are merged. This system is adapted to provide icons in the user interface that describe the original key performance indicators (CPRs) and user-modified CPRs. When a user modifies the original CPR object to create a customized CPR, its icon changes to visually indicate that the user has modified the CPR.

[0170] 27. A non-temporary computer-readable storage medium as described in Clause 26, which may be used in relation to the presentation layer of the data analytics environment to prepare a user interface deck, cards, dashboard, or other visualization associated with customer data and maintained within the data analytics environment.

[0171] 28. The System is provided in a cloud or multi-tenant environment and is a non-temporary computer-readable storage medium as described in Clause 26.

[0172] 29. Customized key performance indicators are stored in JSON format, which is used to provide information returned to the user interface by the database and to indicate when the 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 the indication of the key performance indicator, including its icon displayed in the user interface, on a non-temporary computer-readable storage medium as described in Clause 26.

[0173] 30. A non-temporary computer-readable storage medium as described in Clause 26, from which a sequence of key performance indicators (KPIs) can be viewed, from which a specific KPI can be selected for customization, an icon is provided to indicate which KPI has been customized, and at a later point the user may choose to revert a customized KPI back to its original KPI, and the icon associated with that KPI reverts to its original icon.

[0174] According to various embodiments, the teachings herein may be conveniently implemented by one or more conventional general-purpose or dedicated digital computers, computing devices, machines, or microprocessors, including one or more processors, memory, and / or computer-readable storage media programmed in accordance with the teachings herein. A programmer skilled in the art can readily provide appropriate software coding based on the teachings herein, as will be apparent to a person proficient in software technology.

[0175] In some embodiments, the present invention includes a computer program product which is a non-temporary computer-readable storage medium (or multiple computer-readable storage mediums) storing instructions. A computer can be programmed to use the computer program product to perform any of the operations of this teaching. For example, such storage mediums may include, but are not limited to, hard disk drives, hard disks, fixed disks or other electromechanical data storage devices, any type of disk including floppy disks, optical disks, DVDs, CD-ROMs, microdrives and magneto-optical disks, ROMs, RAMs, EPROMs, EEPROMs, DRAMs, VRAMs, flash memory devices, magnetic or optical cards, nanosystems, or other types of storage mediums or devices suitable for temporarily storing instructions and / or data.

[0176] The above description is provided for illustrative and illustrative purposes only. It is not intended to be comprehensive or to limit the scope of protection to the exact form disclosed. Many changes and modifications will be apparent to those skilled in the art.

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

[0178] Embodiments have been selected and described to best illustrate the principles of this teaching and their practical applications. This will enable those skilled in the art to understand various embodiments and, in addition, various modifications suitable for specific applications. The scope of this disclosure is indicated by the appended claims and their equivalents.< / metadata>

Claims

1. A system for providing customization of key performance indicators (KPIs) in an analytical application environment, including a user interface for modifying key performance indicator objects. A computer containing one or more processors provides access to an analytical application environment, The system enables customization of key performance indicators (CPRs) derived from multiple layers that provide customized CPRs based on the original version. The one or more processors, for the purpose of customization, accept input of metrics to be added to the original key performance indicator definition at runtime, One or more processors generate a customized key performance indicator object by merging the original key performance indicator definition with the additional indicators. The system is adapted to provide the user interface with icons describing the original key performance indicator and the user-modified key performance indicator, and when a user modifies the 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.

2. The system according to claim 1, wherein the key performance indicator model may be used in relation to the presentation layer of the data analytics environment to prepare a user interface deck, cards, dashboard, or other visualization associated with customer data and maintained within the data analytics environment.

3. The system described above is provided in a cloud or multi-tenant environment, as described in claim 1 or 2.

4. The system according to claim 2, wherein the customized key performance indicators are stored in JSON format, the JSON format is used to provide information returned to the user interface by the database 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 the indication of the key performance indicator, including its icon displayed in the user interface.

5. The system according to any one of claims 1 to 4, wherein an array of key performance indicators (KPIs) can be viewed, a specific KPI can be selected from the array for customization, an icon is provided to indicate which KPI has been customized, and at a later point the user can choose to revert the customized KPI back to its original KPI, and the icon associated with that KPI reverts to its original icon.

6. A method for providing customization of key performance indicators (KPIs) in an analytical application environment, comprising a user interface for modifying key performance indicator objects, the method being: A computer containing one or more processors provides access to an analytical application environment, The method includes providing a customization of key performance indicators derived from multiple layers that provide customized key performance indicators based on the original version, wherein providing the customization includes accepting input of indicators to be added to the original key performance indicator definition at runtime, and the method further includes generating a customized key performance indicator object by merging the original key performance indicator definition and the added indicators. A method comprising providing icons in the user interface that describe the original key performance indicator and the user-modified key performance indicator, wherein when a user modifies the 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.

7. The method according to claim 6, wherein the key performance indicator model may be used in relation to the presentation layer of the data analytics environment to prepare a user interface deck, cards, dashboard, or other visualization associated with customer data and maintained within the data analytics environment.

8. The method according to claim 6 or 7, wherein the system is provided in a cloud or multi-tenant environment.

9. The method according to claim 7, wherein the customized key performance indicators are stored in JSON format, the JSON format is used to provide information returned to the user interface by the database 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 the indication of the key performance indicator, including its icon displayed in the user interface.

10. The method according to any one of claims 6 to 9, wherein an array of key performance indicators (KPIs) can be viewed, a specific KPI can be selected from the array for customization, an icon is provided to indicate which KPI has been customized, and at a later point the user can choose to revert the customized KPI back to its original KPI, and the icon associated with that KPI reverts to its original icon.

11. A computer program for causing a computer to perform the method described in any one of claims 6 to 10.

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