In some implementations, a device may store a set of data in a first database associated with a fixed storage duration and a storage parameter that restricts access associated with adding or modifying information stored in the first database. The device may process a subset of data from the set of data, wherein processing the subset of data includes performing one or more data processing operations performed via data processing operation documentation that defines the one or more data processing operations. The device may store the data processing operation documentation in a second database associated with a variable storage duration for data stored in the second database. The device may provide the first database and the second database as data sources for a data searching application to enable the first database and the second database to be searchable via a dashboard associated with the data searching application.

A server in a cloud-based environment interfaces with storage devices that store shared content accessible by two or more users. Individual items within the shared content are associated with respective object metadata that is also stored in the cloud-based environment. Download requests initiate downloads of instances of a virtual file system module to two or more user devices associated with two or more users. The downloaded virtual file system modules capture local metadata that pertains to local object operations directed by the users over the shared content. Changed object metadata attributes are delivered to the server and to other user devices that are accessing the shared content. Peer-to-peer connections can be established between the two or more user devices. Object can be divided into smaller portions such that processing the individual smaller portions of a larger object reduces the likelihood of a conflict between user operations over the shared content.

A process for recommending pre-constructed queries in data analytics includes writing different records to a correlation data structure correlating different data classifications of data to different queries and, subsequent to the writing, establishing a communicative connection by a data analytics application to an underlying database. Thereafter, a data model for data in the database may be constructed in the data analytics application and at least one of the different queries may be selected in the correlation data structure that correlates to the classification of the data in the data model. Finally, the selected one of the different queries may be displayed in the data analytics application to an end user so as to provide an intelligent recommendation for the addition of the selected one of the different queries without requiring the end user to alone and without assistance discover the suitability of the selected one of the different queries.

Some embodiments provide a method for quantifying the workload placed on a database by an application. The method identifies a first group of database queries that the application directed towards the database. The method produces a second group of queries by removing, from the first group of queries, queries that are duplicates based on the semantic structure of the queries. Based on a set of properties of the second group of queries, the method computes a complexity indicator that represents a complexity expression of the second group of queries.

Embodiments of the present disclosure may provide a data clean room architecture that dynamically restricts data included in the clean room. The data clean room architecture can implement row access policy or dynamic data masking for row and column based restrictions of data provided through the clean room. The data clean room architecture can provide a limited set of data that does not require obfuscation of data for direction matching and correlation of data in the different datasets, such as matching user identifiers or emails.

The present invention extends to methods, systems, and computer program products for executed stored procedures at parallel databases. Stored procedures are transformed so that execution of the stored procedure is split between a standalone database server and a parallel database coordinator. Execution of the stored procedure is initiated at the standalone database server. At execution time, control-flow statements, variable assignment, expression evaluation, etc., are handled by the standalone database server. SQL statements are passed from the standalone database server to the database for the execution. Results from executed SQL statements can be returned to the standalone database server or to a client. The parallel database coordinator can be added as a linked server to the standalone database server. In some embodiments, a session token is used to share session state between different parties.

Methods, systems, and computer-readable media for generating a statistically covaried machine learning model for performance measurement of service providers. The method receives a configuration file that includes one or more parameters associated with a plurality of individuals and parses it to generate and executing the database query on input data to generate sets of tabulated data of individuals of the plurality of individuals. The method next determines one or more measures of service providers listed in the configuration file using two or more tabulated data of individuals from the sets of tabulated data of individuals. The method finally generates a covaried machine learning model by training a machine learning model by statistically covarying measures and using them as training data.

Aspects of the disclosure relate to a machine learning based identification and classification of database commands. A computing platform may retrieve, by a computing device and from a first database of a plurality of databases, a database command. Subsequently, the computing platform may identify, by the computing device and for the database command and based on a machine learning model, one or more database commands from the plurality of databases, wherein the one or more database commands perform operations similar to the database command. Then, the computing platform may determine, by the computing device and for the database command, a security score indicative of a level of vulnerability associated with the database command. Subsequently, the computing platform may provide, via an interactive graphical user interface, the database command and the security score.

Some embodiments provide a method for analyzing database queries performed on a database. The method receives a log that includes a set of database queries that were performed on the database. The method identifies, from the log, two or more subsets of queries that are each associated with a different connection session between the database and a set of client applications, where each subset is associated with a set of temporary session objects that are not associated with queries in the other subsets of queries. The method performs a separate query interpretation process on each subset of queries to quantify the impact of performing the queries on the database during the connection sessions, where the query interpretation processes are performed separately in order to avoid errors associated with the temporary objects.

A system and method are described to create and use an Integrated Object Environment (IOE) running in a graph database environment. Uses include storing, revealing and maintaining value and risk of information assets, such as the topology of an analytical infrastructure in query-driven, graph database. A graphical user interface is described to permit importation, viewing, modification and querying in the IOE.