A method implements a dashboard runtime that comprises a custom visualization component to render a visual representation of a data items of one or more queried datasets in a GUI; at least one query associated with at least the custom component; and an API to provide communication between the custom component and the at least one query. The API detects a user interaction with of a portion of the custom component via a first message that informs the dashboard runtime of the detected user interaction; passes a second message to the at least one query instructing the at least one query to rerun to receive an updated query dataset; and passes the updated dataset via a third message to the custom component and to any other components associated with the at least one query, such that the custom component and the other components automatically render updated visual representations of the updated dataset.

A method, computer program and apparatus is disclosed. The method, performed by one or more processors, may comprise receiving, from one or more predetermined organizations, datasets representing entities and datasets representing one or more tasks for those entities and storing in a database, in accordance with an ontology which is common to the organizations, the received one or more datasets as data objects, the ontology defining properties of data objects and relationships between the data objects. The method may also comprise mapping the data objects stored in the database to the organization from which the one or more datasets were received and receiving, through a querying application, a query from a user of one of the predetermined organizations to view one or more data objects relating to a task. The method may also comprise identifying the organization to which the user is associated, generating, based on the mapping, a view including at least the one or more task data objects associated with the identified organization and not data objects associated with other organizations and displaying the view on a user interface.

A unified graph query system provides an abstraction layer that increases the interoperability of different graph technologies by exposing graphs stored in graph databases using a unified query language. The abstraction layer generates graph models for each of the available graph databases and extracts a graph component and other source data used to identify the source of the data requested by a query. The unified graph query system executes the query across the multiple graphs included in different graph databases by using the graph models to locate the graph component in each of the multiple graphs and extract the feature data associated with the graph component. The feature data is used to generate features that are used by a machine learning service to train machine learning models and is also used to make predictions in real time.

Systems and methods for range programming using a search query are disclosed. A method for range programming using a search query includes determining whether the search query comprises a range operation and identifying a target application to launch using a search application which is separate from the target application and based on the search query. A range of results to process with the target application can be identified using the search application and based on the search query. The results can be separately within the range in the context of the target application.

In an example embodiment, rather than passing SQL statements directly from an application runtime to a relational database, the SQL statements are first passed to a wrapper functionality. The wrapper functionality takes the uncompelled SQL statements and arguments that need to be passed for the SQL statement as input parameters, executes the statement, and returns the results. This is accomplished by generating a hash identification out of the string SQL statement. The wrapper functionality then looks for a hash identification of an input SQL statement. If it exists, then a corresponding object in the database can be retrieved and executed. If the hash identification is not found, a database object is created that performs the same functionality as the SQL statement. At this time, the SQL statement is also precompiled, and an execution plan created either by the wrapper functionality or the relational database, or both).

A data partition storage system is provided. The system includes: a data analysis device, configured to determine, according to a data feature of target data comprised in a database, a heat level corresponding to the target data; and a database kernel, deployed on a target device different from the data analysis device to form the database, and configured to: acquire the heat level corresponding to the target data transmitted by the data analysis device; and store the target data in a storage area corresponding to the heat level.

An efficient blend of home/personal and work/productivity related content based on a user's intent is provided, wherein the user's intent can be determined based on context information, learned user interaction patterns, and historical work and home characteristics and patterns. The system is individualized to the user and operative to generate a user experience that provides a blend of relevant home/personal and work/productivity related information to the user based on the user's current work and life characteristics. From a determined user intent, various aspects provide personalized computing experiences tailored to the user and, in some examples, incorporation of the user's patterns into an efficient blend of personal and productivity workflows. In further examples, the blend of home/personal and work/productivity related content and workflows are selectively displayed to the user such that screen resources are efficiently and advantageously allocated based on a determined relevance to the user's current work and life characteristics.

Described is a system, method, and computer program product to perform bi-directional mapping of hierarchical data (e.g. JSON, XML) to database object types (e.g., user defined database object types).

As described herein, a system, method, and computer program are provided for normalizing a JSON structure. In use, input defining at least one entity type of a target data structure is received. A source JSON structure is identified. The source JSON structure is traversed for a particular JSON data type to map values in the source JSON structure to corresponding entities of the target data structure based on the at least one entity type defined for the target data structure, where each entity of the target data structure is defined using a relative path between nodes of the source JSON structure.

A new type system may be added to a type registry for a data processing service. A request to add the new type system may be received that describes the new type system for a data store. The new type system may be used to perform a data processing job that accesses the data store to obtain or store data as a source or target data store.