Abstract: Methods, systems, and computer-readable storage media for receiving user input indicating a value of a first setting of one or more settings, the first setting defining a data integrity scenario that is be applied during a query session with a database system, the data integrity scenario defining data sources for reading data in response to one or more navigation requests, if a concurrent change occurs in the database system, receiving a query, reading, data from one or more data sources based on the query and the first setting, selectively caching at least a portion of the data based on the first setting, and providing a result for display to a user that submitted the query.

Abstract: Methods, systems, and computer-readable storage media for receiving user input indicating a value of a first setting of one or more settings, the first setting defining a data integrity scenario that is be applied during a query session with a database system, the data integrity scenario defining data sources for reading data in response to one or more navigation requests, if a concurrent change occurs in the database system, receiving a query, reading, data from one or more data sources based on the query and the first setting, selectively caching at least a portion of the data based on the first setting, and providing a result for display to a user that submitted the query.

Abstract: A central data warehouse includes embedded data marts. These embedded data marts, referred to as workspaces, are assigned centrally manage data by reference only but rely directly on the centrally managed data and the underlying infrastructure. Workspaces still allow departments in an enterprise to perform certain actions on their own (like adding new data and building new models) without having to instantiate copies of the centrally managed data in a locally managed data mart.

Abstract: A central data warehouse includes embedded data marts. These embedded data marts, referred to as workspaces, are assigned centrally manage data by reference only but rely directly on the centrally managed data and the underlying infrastructure. Workspaces still allow departments in an enterprise to perform certain actions on their own (like adding new data and building new models) without having to instantiate copies of the centrally managed data in a locally managed data mart.