Reimagining the Predictive Experience
The Advanced Analytics mission is to help companies improve their bottom line by making their business processes and apps better with predictive techniques. Here are the key concepts of our approach...
 | Embedded in Business Processes and Apps | ||
| The real value of predictive analytics can only be achieved by embedding them into apps and tools used by the business users on a daily basis. The integration must be done in such a way that 1- business applications offer specific workflows with off-the-shelf predictive functions; 2- Data scientists have the option of replacing them by proprietary and more advanced predictive functions. | |||
The Predictive Factory |  | ||
No coding, just configuration! Full predictive lifecycle – from data preparation, model building/rebuilding, model evaluation, model deployment and monitoring, versioning Modeling automation – Ability to automate models for multiples segments by creating the first one and letting Predictive Analytics complete the task Inclusive – embrace collaborative approach among non experts and experts | |||
 | Low and High Touch User Experiences | ||
Low touch user interface using wizard-based approach and automated High touch (visual data pipeline framework) user interface supporting open languages (such as R, Scala, etc.) Interoperability between both modes so results – scores, prediction, forecasts, etc... can be shared easily among coworkers and teams | |||
Predictive Intellectual Property |  | ||
Generic proprietary algorithms providing very good results in most data situations with no parameter tuning Niche proprietary algorithms providing unmatched results in unique business context / data situation Niche predictive IP to be available via a marketplace opened to partners and ISV | |||
 | Cloud | ||
All-in-one Cloud for Analytics initially targeting analysts and business users with Exploratory Analytics Model consumption for pre-packaged business scenarios HCP Predictive Services targeting partners and integrators Framework for model consumption in business applications on-demand applications | |||
On Premise |  | ||
Will be compatible and interoperable with the previous SAP investments: Analytics platform (known as BI Platform) SAP HANA computing platform – especially through XS Advanced and SAP HANA Streaming | |||
 | Big Data | ||
Data Preparation compatible with ultra-wide data sets Distribution of algorithms on scale-out architectures Integration into Big Data streaming environments | |||
- SAP Managed Tags:
