SAP Updates Data Visualization and Predictive Analytics Solutions

SAP has made updates to its Lumira software and InfiniteInsight solution that extend capabilities in enterprise business intelligence and agile visualizations as well as predictive analytics.

The new release of SAP Lumira – 1.1.8 – provides the ability for users to create interactive stories from their desktop, server, or the cloud and present insights with customizable infographics, including support for custom charts and ESRI maps. In addition, the latest innovations with Lumira bring together trusted data discovery with the ability to create compelling visualizations and uncover hidden insights in the data, and allows that to be shared with the Business Objects 4.1  BI Platform, noted Nic Smith, senior director of marketing for analytics at SAP. “This brings together the both worlds - the best of agile visualizations with Lumira and being able to manage, secure, and provide the scale of performance, as well as the administration and trust of the data with the BI platform.”

SAP InfiniteInsight (formerly KXEN) helps automate the effort involved with predictive analytics so that users can make forward-looking decisions. Updates to InfiniteInsight 7.0 include extended database support covering Hadoop Hive 11 and 12 and the Greenplum database. In addition, the user interface has been improved from an accessibility and usability point of view, as well as from a compliance standpoint, most notably with support for Kerberos authentication, said  Chandran Saravana, senior director of solution marketing for advanced analytics at SAP.

The 7.0 release also expands the use of geo-referenced data as input in models. The software can combine multiple variables containing latitude and longitude to create variables that can be used in predictive models. Combined with SAP InfiniteInsight social application users can make the most of geographic data, extract the sequence of places visited, and perform location-based segmentation. “Everyone today has a connected device, and time and location are becoming two important attributes regardless of what type of analysis is being done.  Geo-location is a critical factor as far as activities such as engaging with customers or just doing fraud detection,” observed Saravan.

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