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I saw this at ASUG Annual Conference but didn’t have the details to share anything until SAP provided a webcast last week on this.  Please note ASUG has a related webcast you can register for here – it is being held tomorrow.

Figure 1, Source: SAP

There are 2 types of users using predictive

One is citizen data scientist

Analytics product includes data prep – 70 to 80% of time spent on data prep

Expert analytics toolset for the data scientist

Output of predictive apps will be included in SAP applications such as hybris, SAP Analytics Cloud

Figure 2 – source, SAP

SAP investment priorities are in SAP Analytics Cloud, providing an end to end solution in the cloud

Building Predictive Analytics Integrator – embed predictive results in applications

Figure 3 – source, SAP

Introduce SAP Cloud Smart Predict – making predictive capabilities simple for the business analyst

Smart predict, with results, can be served up in platform, models updated


Figure 4, source, SAP
Roadmap, from 2016, had a standalone product

Where going now, enabling citizen data scientist to leverage SAP Analytics Cloud, with user-
driven model development, build your own models without degree in statistics

Figure 5, source, SAP

Why important? Cycle behind putting products in one platform

Visualize, learning from information, predict what happens next, plan what happens next

Prediction is a suggestion

Don’t have to move data around; all in one product


Figure 6, source, SAP

Smart predict product plan is above

Algorithms available in Q3, with Predictive Composer, invest in User Experience

Consumer scores in stories

Q4 – expect to have clustering in Smart Predict, live connections, scoring in data sources

Future – schedule training, test model quality

Upcoming Webinars

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