Abstract: In accordance with an embodiment, described herein is a system and method for loading and transforming data to a cloud database, using a hybrid set-based extract, load, transform approach. During the loading and transforming of large amounts of data, from one or more data sources, a data synchronization application sends small batches of data, in parallel streams, to the database, which operates as a transformation engine to load the data. Each stream can be associated with a separate staging table in the database. For each staging table, the subset of data therein is transformed and loaded, before the next subset is processed. A transform and merge process operating at the database can then be used to transform and merge the data, from each of the staging tables, to the target table.

Abstract: In accordance with an embodiment, described herein is a system and method for providing query acceleration with a computing environment such as, for example, a business intelligence environment, database, data warehouse, or other type of environment that supports data analytics. A middle layer is provided as a long-term table data storage format; and one more acceleration formats, or acceleration tables, can be periodically regenerated from the middle layer, wherein a determination can be made as to whether an accelerated table exists for a dataset table, and if so, then the accelerated table is used to process the query.

Abstract: In accordance with an embodiment, described herein is a system and method for loading and transforming data to a cloud database, using a hybrid set-based extract, load, transform approach. During the loading and transforming of large amounts of data, from one or more data sources, a data synchronization application sends small batches of data, in parallel streams, to the database, which operates as a transformation engine to load the data. Each stream can be associated with a separate staging table in the database. For each staging table, the subset of data therein is transformed and loaded, before the next subset is processed. A transform and merge process operating at the database can then be used to transform and merge the data, from each of the staging tables, to the target table.

Abstract: In accordance with an embodiment, described herein is a system and method for loading and transforming data to a cloud database, using a hybrid set-based extract, load, transform approach. During the loading and transforming of large amounts of data, from one or more data sources, a data synchronization application sends small batches of data, in parallel streams, to the database, which operates as a transformation engine to load the data. Each stream can be associated with a separate staging table in the database. For each staging table, the subset of data therein is transformed and loaded, before the next subset is processed. A transform and merge process operating at the database can then be used to transform and merge the data, from each of the staging tables, to the target table.

Abstract: A method of on-demand model navigation includes providing a graphical explorer layout (GEL) algorithm for user exploring within an enterprise process model including assets as nodes, relationships between assets as links between nodes, and related node information. The GEL triggers on the display device displaying an initial dashboard fixed view including ?2 of the nodes (shown nodes), a context menu and a menu for the links. Responsive to selecting a first of the shown nodes (first selected node) from the dashboard fixed view, displaying a first on-demand enterprise model graph showing the first selected node as an anchor node along with related nodes with links therebetween shown. Responsive to selecting a second of the shown nodes, a second on-demand enterprise model graph having ?two levels can be displayed with the second selected node as an anchor node along with related nodes with the links therebetween shown.

Abstract: In accordance with an embodiment, described herein is a system and method for loading and transforming data to a cloud database, using a hybrid set-based extract, load, transform approach. During the loading and transforming of large amounts of data, from one or more data sources, a data synchronization application sends small batches of data, in parallel streams, to the database, which operates as a transformation engine to load the data. Each stream can be associated with a separate staging table in the database. For each staging table, the subset of data therein is transformed and loaded, before the next subset is processed. A transform and merge process operating at the database can then be used to transform and merge the data, from each of the staging tables, to the target table.

Abstract: A method of on-demand model navigation includes providing a graphical explorer layout (GEL) algorithm for user exploring within an enterprise process model including assets as nodes, relationships between assets as links between nodes, and related node information. The GEL triggers on the display device displaying an initial dashboard fixed view including ?2 of the nodes (shown nodes), a context menu and a menu for the links. Responsive to selecting a first of the shown nodes (first selected node) from the dashboard fixed view, displaying a first on-demand enterprise model graph showing the first selected node as an anchor node along with related nodes with links therebetween shown. Responsive to selecting a second of the shown nodes, a second on-demand enterprise model graph having ? two levels can be displayed with the second selected node as an anchor node along with related nodes with the links therebetween shown.