Abstract: In accordance with one aspect of the present disclosure, a request to provide recommendations of data enrichments for a database is received at a recommendation engine. The recommendation engine may perform static and dynamic analysis of data associated with the database and may further refine recommendations based on policies. The recommendation engine may then provide the recommendations, if any, of data enrichments to allow a software developer, for example, to indicate whether the data enrichments are to be used.

Abstract: In accordance with one aspect of the present disclosure, a request to provide recommendations of data enrichments for a database is received at a recommendation engine. The recommendation engine may perform static and dynamic analysis of data associated with the database and may further refine recommendations based on policies. The recommendation engine may then provide the recommendations, if any, of data enrichments to allow a software developer, for example, to indicate whether the data enrichments are to be used.

Abstract: In accordance with one aspect of the present disclosure, a request to provide recommendations of data enrichments for a database is received at a recommendation engine. The recommendation engine may perform static and dynamic analysis of data associated with the database and may further refine recommendations based on policies. The recommendation engine may then provide the recommendations, if any, of data enrichments to allow a software developer, for example, to indicate whether the data enrichments are to be used.

Abstract: Aspects of the subject matter described herein relate to recommending data sources. In aspects, a request to provide recommendations of data enrichments for a database is received at a recommendation engine. The recommendation engine may perform static and dynamic analysis of data associated with the database and may further refine recommendations based on policies. The recommendation engine may then provide the recommendations, if any, of data enrichments to allow a software developer, for example, to indicate whether the data enrichments are to be used.

Abstract: The present invention extends to methods, systems, and computer program products for recommending data sources. A request to provide recommendations of data enrichments for a database is received at a recommendation engine. The recommendation engine may perform static and dynamic analysis of data associated with the database and may further refine recommendations based on policies. The recommendation engine may then provide the recommendations, if any, of data enrichments to allow a software developer, for example, to indicate whether the data enrichments are to be used.

Abstract: The subject disclosure is directed towards enriching database query responses using data from external data sources. When processing a database query seeking enriched data from an external data source, a request is communicated to the external data source based on the database query. An enriched database query response is generated based on data provided by the external data source. The enriched database query response may be combined with data returned via an internal database query operation, and/or inserted into a local database table.

Abstract: The subject disclosure is directed towards enriching database query responses using data from external data sources. When processing a database query seeking enriched data from an external data source, a request is communicated to the external data source based on the database query. An enriched database query response is generated based on data provided by the external data source. The enriched database query response may be combined with data returned via an internal database query operation, and/or inserted into a local database table.

Abstract: The subject disclosure is directed towards enriching database query responses using data from external data sources. When processing a database query seeking enriched data from an external data source, a request is communicated to the external data source based on the database query. An enriched database query response is generated based on data provided by the external data source. The enriched database query response may be combined with data returned via an internal database query operation, and/or inserted into a local database table.

Abstract: The subject disclosure is directed towards enriching database query responses using data from external data sources. When processing a database query seeking enriched data from an external data source, a request is communicated to the external data source based on the database query. An enriched database query response is generated based on data provided by the external data source. The enriched database query response may be combined with data returned via an internal database query operation, and/or inserted into a local database table.

Abstract: The present invention extends to methods, systems, and computer program products for intelligently recommending schemas based on user input that defines a portion of a data structure. An intelligent auto-complete function can identify characteristics of the user input and, based on these characteristics, recommend schemas that are most likely to be selected by the user to complete the data structure or portion of the data structure. The identified characteristics of the user input can be compared to characteristics of defined schemas or of other data structures to identify schemas that are most likely to match the user's intent. These schemas are then recommended to the user. Such schemas can define the recommended shape of the data structure being defined, including data types for a particular column, columns to add to the data structure, or can define additional data structures to be added such as additional tables to a database.

Abstract: The present invention extends to methods, systems, and computer program products for intelligently recommending schemas based on user input that defines a portion of a data structure. An intelligent auto-complete function can identify characteristics of the user input and, based on these characteristics, recommend schemas that are most likely to be selected by the user to complete the data structure or portion of the data structure. The identified characteristics of the user input can be compared to characteristics of defined schemas or of other data structures to identify schemas that are most likely to match the user's intent. These schemas are then recommended to the user. Such schemas can define the recommended shape of the data structure being defined, including data types for a particular column, columns to add to the data structure, or can define additional data structures to be added such as additional tables to a database.

Abstract: Embodiments are directed to selecting and applying data-specific presentations, to adaptively selecting visual presentations based on historical data and to providing rendering hints for data presentations. In one scenario, a computer system receives an indication that a visual presentation is to be applied to a specified portion of data. The computer system analyzes the specified data to determine which of a plurality of data presentations is most relevant for the specified data. The relevance is based on relevancy factors including one or more of the following: end-user profile, structure of the specified data and patterns within the specified data. The computer system then applies the determined appropriate visual presentation to the specified data.

Abstract: The present invention extends to methods, systems, and computer program products for recommending data based on user and data attributes. User information and accessed data sets are periodically (and possibly automatically) accessed and updated. Source attributes are derived from user information and accessed data sets. Target attributes are derived from data directories and data services. Source attributes for an accessed data set are used along target attributes for a data directory or data service to determine the desirability of data directory or data service as a source of data relevant to the accessed data set. The data directory and/or data service can be recommended as able to provide relevant data. Accordingly, recommend relevant data can be recommended to a user without the user having to expressly search for the relevant data or even know that the relevant data exists.

Abstract: The subject disclosure is directed towards enriching database query responses using data from external data sources. When processing a database query seeking enriched data from an external data source, a request is communicated to the external data source based on the database query. An enriched database query response is generated based on data provided by the external data source. The enriched database query response may be combined with data returned via an internal database query operation, and/or inserted into a local database table.

Abstract: The subject disclosure is directed towards enriching database query responses using data from external data sources. When processing a database query seeking enriched data from an external data source, a request is communicated to the external data source based on the database query. An enriched database query response is generated based on data provided by the external data source. The enriched database query response may be combined with data returned via an internal database query operation, and/or inserted into a local database table.

Abstract: Embodiments are directed to selecting and applying data-specific presentations, to adaptively selecting visual presentations based on historical data and to providing rendering hints for data presentations. In one scenario, a computer system receives an indication that a visual presentation is to be applied to a specified portion of data. The computer system analyzes the specified data to determine which of a plurality of data presentations is most relevant for the specified data. The relevance is based on relevancy factors including one or more of the following: end-user profile, structure of the specified data and patterns within the specified data. The computer system then applies the determined appropriate visual presentation to the specified data.

Abstract: The present invention extends to methods, systems, and computer program products for intelligently recommending schemas based on user input that defines a portion of a data structure. An intelligent auto-complete function can identify characteristics of the user input and, based on these characteristics, recommend schemas that are most likely to be selected by the user to complete the data structure or portion of the data structure. The identified characteristics of the user input can be compared to characteristics of defined schemas or of other data structures to identify schemas that are most likely to match the user's intent. These schemas are then recommended to the user. Such schemas can define the recommended shape of the data structure being defined, including data types for a particular column, columns to add to the data structure, or can define additional data structures to be added such as additional tables to a database.

Abstract: The present invention extends to methods, systems, and computer program products for discovering and consuming related data. Users can find data related/relevant to an accessed dataset without leaving the context of their application. A service analyzes and understands (classifies) the dataset as well as user profile information and environmental information (e.g., operating system in use, task being performed, etc.). The service displays recommendations for related/relevant data and/or related/relevant data services within the application (e.g., within a spreadsheet, database, file system, etc.). In response to user selection of a recommendation, related/relevant data (either directly or from a data service) is transferred into the application. Accordingly, relevant/related data can be transferred into an application without a user having to leave the application to search for the data.

Abstract: The present invention extends to methods, systems, and computer program products for recommending data based on user and data attributes. User information and accessed data sets are periodically (and possibly automatically) accessed and updated. Source attributes are derived from user information and accessed data sets. Target attributes are derived from data directories and data services. Source attributes for an accessed data set are used along target attributes for a data directory or data service to determine the desirability of data directory or data service as a source of data relevant to the accessed data set. The data directory and/or data service can be recommended as able to provide relevant data. Accordingly, recommend relevant data can be recommended to a user without the user having to expressly search for the relevant data or even know that the relevant data exists.

Abstract: The subject disclosure is directed towards enriching database query responses using data from external data sources. When processing a database query seeking enriched data from an external data source, a request is communicated to the external data source based on the database query. An enriched database query response is generated based on data provided by the external data source. The enriched database query response may be combined with data returned via an internal database query operation, and/or inserted into a local database table.