First Look: SAP Predictive Analytics Update
I got an update from SAP on their Predictive Analytics products. Back in December I got a briefing on the Windows client (that went GA in November 2012) and the SAP HANA (SAP’s in-memory database) libraries related to it.
I got an update from SAP on their Predictive Analytics products. Back in December I got a briefing on the Windows client (that went GA in November 2012) and the SAP HANA (SAP’s in-memory database) libraries related to it. SAP, like me, is seeing a lot of demand for predictive analytics with existing clients needing to scale up to more use cases and new clients driven to predictive analytics by their interest in Big Data.
SAP has a broad spectrum of BI/analytics users across IT, competency centers and lines of business. SAP wants to bring all these various users up the analytic learning curve to predictive analytics. SAP sees various market segments:
- Customized hand coded models using a script-based approach
What I would regard as the approach of traditional predictive analytic developers.
- Customized application models relying on more workflow and managed production of custom models
A more industrialized mindset to producing and managing lots of predictive analytic models.
- Automated Analytical Software
Embedding predictive analytics into automated decisions, what I would call Decision Management
- Prebuilt Analytical Apps
Including pre-configured Decision Management Systems
Key pain points remain the tension between business/domain expertise, analytic expertise and IT expertise as well as the focus of many predictive analytic tools on highly skilled modelers.
Challenges include the proliferation of predictive analytic models as companies become committed to predictive analytics (multiple segments, channels and products result in dozens or hundreds of models), the trend towards real-time decision-making and the challenges of new and different data sources (Big Data) – Model Management, Decision Management and Big Data Management are key.
SAP Advanced Analytics therefore contains:
- SAP Lumira for exploration, discovery, collaboration
This has now been extended to support predictive analytic workflows.
- SAP Predictive Analytics for visualization and creation of predictive analytic models
This has been extended to improve its support for R.
- SAP Hana for in-memory processing
SAP’s in-memory columnar database with native predictive and machine learning algorithms for in-database processing, R integration and now able to federate data from Hadoop, Sybase IQ, Sybase ASE and Teradata data sources.
- SAP RDS (Rapid Deployment Services) preconfigured content to accelerate projects
- SAP PIO (Predictive Industry Organization) to provide predictive analytic and industry expertise
SAP sees a wide range of personas involved in the lifecycle of a model – from business analysts to data scientists/data miners, application developers and IT. The tools are designed to support this whole lifecycle and all these roles. A single set of visualization tools work across the various environments and a wide range of data connectors allow the same data to be presented in different environments.
You can get more information on SAP Predictive Analysis here:www.sap.com/predictive-analysis and SAP is one of the vendors in our Decision Management Systems Platform Technology Report.
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