Sap Se

Swati Krishna Setty

Dharmesh Rana

Arpitha A Shetty

Tejram Jagannath Sonwane

Amrita Prabhakaran

Arjun Krishnakumar

Soumya Patil

Jagadish Radhakrishnan

Swetha Konduru

A document is received, the document including metadata for a data visualization of a data set. The data set includes a plurality of data columns, each of the plurality of columns having a column name and a plurality of data values. A first set of columns of the plurality of columns is present in the data visualization. The first set of columns is determined based on the metadata. A second set of columns of the plurality of columns is determined, where the second set of columns includes remaining columns of the plurality of columns excluding the first set of columns. The data set is ordered by having the first set of columns prior to the second set of columns. A composite index is generated on the ordered data set.

Performance improvement in data visualization filters

In offline access of data in mobile devices, a request to access a document is received at a mobile server. The document is fetched from a BI platform to the mobile server. Plurality of requests is sent from the mobile server to the BI platform to retrieve data packages from the BI platform. The data packages is converted to a plurality relational database management tables at the mobile server. The plurality of relational database management tables is compressed to a compressed database. The compressed database is sent to the mobile device and stored. A new request is received at the mobile device for operations on the document. Based on the new request, operations are performed on the document based on the compressed database stored in the mobile device, when the mobile device is not connected to the mobile server.

Offline access of data in mobile devices

Various embodiments of systems and methods to render data visualizations in different analytical applications are described herein. In one aspect, a request is received to render at least a portion of data visualization by an analytical application. A visualization type and one or more data attributes are retrieved from metadata corresponding to at least the portion of the data visualization. Further, a supporting visualization type is identified in the analytical application corresponding to the visualization type of at least the portion of the data visualization. The retrieved one or more data attributes are mapped to equivalent one or more data attributes in a data source associated with the analytical application. At least the portion of the data visualization is rendered based on the supporting visualization type and the mapped one or more data attributes in a graphical user interface of the analytical application.

Rendering data visualizations in different analytical applications

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Bengaluru, India

Swati Krishna Setty