Sap Se

Business Objects Software Limited

Sumedha Sharma

James LLoyd

Jonathan Tiu

Xing Jin

Xin Qiu

Yang Jin

Sae-Won Om

Mohsen Asadi

Christopher Bolognese

Anthony Kohan

Fangzhou Yin

Anna Chen

Point-of-Interest (POI) data is stored according to a first, POI library as a flat file in a database. An engine is positioned between the POI library and an interface. The interface is configured to interact with data structured in a hierarchical manner and stored according to a second library (e.g., a modeling interface utilizing folders). The engine functions to wrap a POI object taken from a table of the POI library, into an augmented object recognized and handled by the second library of the (hierarchical) interface. To accomplish this, the engine augments the POI table with an additional column that is to be indexed by the second library. In this manner, embodiments may impart additional, hierarchy-based functionality to existing POI handling schemes. Particular embodiments may impart enhanced security (e.g., permissions at the data object-level) to existing POI schemes that implement permissions only at the POI-level and/or at the application-level.

Handling of Point of Interest (POI) data content

In some embodiments, a program generates a query for a set of data from a dataset. The dataset includes a set of measures and a plurality of dimensions for categorizing the set of measures. The set of data includes a set of locations and measure values for a measure in the set of measures categorized according to a dimension in the plurality of dimensions. The program further sends the query to a computing system configured to manage the dataset. The program also receives the set of data from the computing system. The program further renders a visualization comprising a set of visual elements. Each visual element is configured to present a set of measure values for the measure associated with a location in the set of locations. The set of measure values are categorized according to the dimension. The program also presents the visualization on a display of the device.

Generating dimension-based visual elements

Some embodiments provide a non-transitory machine-readable medium that stores a program. The program receives an input specifying a location field of a dataset. In response to the input, the program further retrieves a set of geographical hierarchy definitions. The program also retrieves, from the data source specified for a level in the geographical hierarchy defined by a geographical hierarchy definition in the set of geographical hierarchy definitions, a subset of a set of geometries representing a set of geographical regions belonging to the level in the geographical hierarchy. For each geometry in the subset of the set of geometries, at least one record in the dataset has a spatial point in a location field that falls within the geometry. The program further provides the subset of the set of geometries in a view of a map.

Different data sources for regions in geographical hierarchies

Some embodiments provide a non-transitory machine-readable medium that stores a program executable by at least one processing unit of a device. The program renders a visualization that includes a first set of visual elements. The program further receives a request for measure values categorized according to the first level of dimension values in the first hierarchy of dimension values and a second level of dimension values in the second hierarchy of dimension values. The program also generates a query for a second set of data from the dataset. The program further sends the query to a computing system configured to manage the dataset. The program also receives the second set of data from the computing system. The program further renders a second set of visual elements. The program also replaces the first set of visual elements in the visualization with the second set of visual elements.

Traversing hierarchical dimensions for dimension-based visual elements

In one embodiment, the present disclosure pertains to data import and reconciliation. In one embodiment, a location field is compared against alternative geo-descriptors to link the location fields to areaIDs and geospatial shapes. A similarity search is performed against unmatched location fields. In one example embodiment, a table is generated with unique location IDs, areaIDs, and metadata describing the results of the comparison.

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Vancouver, Canada

Sumedha Sharma