Systems, devices, computer-implemented methods, and tangible non-transitory computer readable media for performing multilayered generation and processing of computer instructions are provided. For example, a computing device may receive a request with instructions in a first computer language, parse the instructions in the first computer language, analyze the instructions in the first computer language in view of information describing structure of a first application, generate instructions in a second computer language different from the first computer language where the instructions in the second computer language are generated based on the instructions in the first computer language and the information describing structure of the first application, obtain a result from a second application where the result comprises information based on the instructions in the second computing language, and provide the result in response to the request comprising the instructions in the first computer language.

Some embodiments involve a method of connecting, by a computerized system, to a database at a source. The computerized system queries the database for data associated with a characteristic and identifies the data. The computerized system organizes the data into a batch based on business-defined rules. The batch condenses a plurality of rows of data in the database associated with the characteristic into one row of data associated with the characteristic. The computerized system transforms the batch into a packet having a text or binary ready-to-consume format and publishes the packet as a ready-to-consume business object.

A method includes receiving, in a first query interface, a query composed by the user by typing commands into a query box of the first query interface and based on the receiving of the query, causing events corresponding to query results of the query to be displayed in the first query interface with fields corresponding to the events. Based on the selection by the user of an option, a second query interface is displayed with a table that includes events that correspond to query results of a loaded query. The table includes columns corresponding to event attributes, rows corresponding to events. Cells are populated with the data items of event attributes, where one of the columns corresponds to a field of the fields displayed in the first query interface. The table also includes interactive regions selectable by the user to add one or more commands to the loaded query.

Operating a low-latency database analysis system with phrase translation may include obtaining a locale-specific phrase localization rule and a canonical phrase localization rule for a phrase, generating a locale-specific index and a locale-specific finite state machine for the locale using the localization definition data and a canonical finite state machine, generating a resolved-request by obtaining a locale-specific token representing locale-specific input data by traversing the locale-specific index, obtaining a canonical token associated with locale-specific token, obtaining a locale-specific phrase by traversing the locale-specific finite state machine, obtaining a canonical phrase corresponding to the locale-specific phrase, the canonical phrase including the canonical token, generate a data-query based on the canonical phrase, obtaining results data responsive to the data expressing the usage intent by executing a query corresponding to the data-query by an in-memory database of the low-latency database analysis system, and outputting the results data for presentation to a user.

In non-limiting examples of the present disclosure, systems, methods and devices for identifying supply chain issues are presented. A first supply chain dataset comprising a plurality of supply chain dimensions may be received. A subset of the dataset may be transformed into plurality of supply chain vectors. A temporal moving average plot may be generated for each supply chain vector in a subset of the plurality of supply chain vectors. A set of rules may be applied to each temporal moving average plot to determine a performance value for each corresponding supply chain vector in the subset. A determination may be made that a performance value for a specific one of the supply chain vectors is below a threshold value. An interactive user interface that indicates the performance value for the specific supply chain vector is below the threshold value may be displayed.

Embodiments of the present invention are directed to facilitating distributed data processing for machine learning. In accordance with aspects of the present disclosure, a set of commands in a query to process at an external computing service is identified. For each command in the set of commands, at least one compute unit including at least one operation to perform at the external computing service is identified. Each of the at least one compute unit associated with each command is analyzed to identify an optimized manner in which to execute the set of commands at the external computing service. An indication of the optimized manner in which to execute the set of commands and a corresponding set of data is provided to the external computing service to utilize for executing the set of commands at the external computing service.

The present invention provides a system, method and software for digitizing and automating an auditing process. The system comprises a computer, a regulations database, a storage database, and a software program. The method includes: providing regulations or standards for a user to select from the regulations database as a focus for an audit; providing a user-selected filtered regulation or standard from the regulations database; presenting the user a plurality of audit questions in the form of an audit row, one audit row at a time; receiving user responses from which at least one standard row item is created and/or updated; and sending one or more of a filtered regulation or standard row item to the storage database as an audit. The system may permit user information updates. After an audit is completed, the system may transfer the audit information into a final report, which may be provided to the user.

Methods, systems, and devices for generating a unique resource identifier are described. According to the techniques described herein, a device (e.g., an application server) may receive a natural language query indicating a query for a value of one or more data records stored in a database table. The database table may be accessible via a target application program interface (API) that is configured as a resource-oriented API. The device may parse the natural language query to identify a set of resources and a set of values corresponding to the set of resources. The device may then identify a hierarchy of the set of resources of the target API and generate the unique resource identifier for the target API to access the value of the one or more data records. The device may generate the unique resource identifier based on the hierarchy of the set of resources.

Some embodiments relate to a method for use in connection with governance of a plurality of data assets managed by a data processing system, the method comprising: using at least one computer hardware processor to perform: accessing a data governance policy comprising a first data standard (e.g., by obtaining information about the first standard stored in a database system); generating a first data asset collection at least in part by automatically selecting, from among the plurality of data assets managed by the data processing system and using at least one data asset criterion, one or more data assets that meet the at least one data asset criterion; associating the first data asset collection with the first data standard; and verifying whether at least one of the one or more data assets in the first data asset collection complies with the first data standard.

Embodiments of the invention are directed to a system, method, or computer program product for providing an intelligent quality accelerator with root mapping system. The system provides a business language model and process automation that stratifies sampling of resource exchanges from products using a machine learning loop and provides an end to end simulation for root cause analysis. In this way, the system provides two layers, a robust sampling and root cause analysis.