Sap Se

Pranav Acharya

Rahul Tiwari

Prasanna Bhat Mavinakuli

Tejram Jagannath Sonwane

Rishi Prajapati

Raghavendra Nagaraja

Tanushree Nandy

Dipti Sengupta

A framework for implementing just-in-time decision support analytics within a business application deployment are provided. In one set of embodiments, the framework enables an application user to be presented with analytics that are in-context and in-place with respect to an operational workflow carried out by the user, where 'in-context' means that the presented analytics are directly relevant to, and tailored for, the specific business context of the user's operational workflow, and 'in-place' means that the analytics are displayed to the user within the same UI/application used to execute the operational workflow, and at the same time the workflow is actually executed. These characteristics advantageously ensure that the user is provided with the insights he/she needs to make confident business decisions and facilitates real-time decision making for time-critical operations.

Framework for just-in-time decision support analytics

Various examples are directed to converting a natural language query to a structured query. The natural language query may comprise a plurality of terms. A natural language system may generate a set of operators and a set of operands based at least in part on the plurality of terms and a metadata dictionary. The natural language system may generate an expression tree based at least in part on the set of operators and the set of operands. The expression tree may comprise a plurality of interconnected nodes. A first node may be associated with a first function corresponding to a first operator of the set of operators and a second node may be associated with a first argument of the first function corresponding to a first operand of the set of operands. The natural language system may generate a query based at least in part on the expression tree.

Natural language query generation

Collaboration application includes a set of shared documents shared with users with different authorization rights. A request to provide relevant shared documents from the set of shared documents is received. Document ranks corresponding to the relevant shared documents are determined. The document ranks are determined based on weighted document factors related to the set of shared documents. A ranked list of the relevant shared documents is provided according to the determined document ranks. User rank for users in relation to a document from the relevant shared documents is determined. The user ranks are determined based on user factors and weights of the user factors. The user factors are related to authorization rights of the users to the document, sharing characteristics of the document and the users, and measurements over interactions of the users with documents from the set of shared documents that are shared with the users.

Ranking of shared documents and users

The disclosure generally describes computer-implemented methods, software, and systems, including a method for providing suggestions. Transaction information is received that is associated with user actions during use by a user of a business intelligence tool. Each user action is associated with an operation in a particular stage of processing on business data obtained from one or more databases. The transaction information for a particular user action includes a user identifier identifying the user performing the particular user action, stage information, an associated operation, and parameters. The transaction information is stored. Subsequent user actions are monitored, including determining a time at which stage conditions match stage information in the stored transaction information. In response to determining matching stage conditions, pertinent transactions are identified. Suggestions are created. Each suggestion is associated with groups of one or more transactions of the pertinent transactions. The suggestions are provided for presentation to the user.

Growing community of inventors

Mumbai, India

Pranav Acharya