SAP’s Charles Gadalla provided this webcast today.
Figure 1: Source: SAP
On the left of Figure 1, high skill sets are needed to be a data scientist, with a masters in statistics.
On the right side, you have business users
Consumers take output from data scientists and take an action.
In the middle: data analysts/business analysts – do more than basic reporting – segmentation, forecasting, in a more sophisticated manner
Figure 2: Source: SAP
Data scientists on the far right of Figure 2 are already well served.
SAP is interested in group in the middle, including embedding the analytics inside the workflow
Figure 3: Source: SAP
Figure 3 shows a paradox that there is a lot of “big data”.
We are using more data today and decisions are made in a much shorter time scale, with a huge increase in speed of algorithms
Every business is being asked to make decisions faster with more data
Why should I care?
Figure 4: Source: SAP
Figure 4 shows that back in December, SAP released a survey, showing competitive “ROI”
Figure 5: Source: SAP
Figure 5 shows Mobilink going through 900TB call data records for communities – 6M communities from these calls
MONext – decision on fraud transactions in milliseconds
Figure 6: Source: SAP
It was on this slide that Charles said “KXEN doesn’t stand for a radio station…it means knowledge extraction engine”. I did not know that.
Figure 7: Source: SAP
Insight from KXEN to view thousands of fields of data; Predictive Analysis was built inside SAP
Charles used as an example if you drink a diet cola on Tuesday at that means you had chips on a Sunday
Another example is to integrate and tell story as Predictive is built on Lumira
Figure 8: Source: SAP
Figure 8 shows data comes in from any of the channels
PAL is on HANA is the implementation on HANA R – maintained by universities and consortium – popular algorithms to use and reuse – execute in memory,
It is based on an open source language
Client tools on top left of Figure 8.
SAP combined Predictive Analysis with Insight in a tool called Insight Modeler
It also includes a line of business application – like Fraud Management, etc.
SAP has RDS solutions using Predictive
They partner with ESRI, SAS
Charles has special speaker from Obama campaign presenting on how the Obama campaign used KXEN to win the 2012 US Presidential election.
Figure 9: Source: SAP
With SAP embedded on HANA, you are not getting the SAS algorithm
You can see the two ways to access HANA in Figure 9
Figure 10: Source: SAP
1) Client side – PA/KXEN – Java based and R based predictive – connect to relational database and CSV
2) Server – Infinite Insight Explorer – connect to database (say Oracle)
a. Factory – model management – how data looked 1-2-3 months
b. Factory scheduling to refresh
c. Infinite Insight Social – trying to detect similar/like-minded people
d. Recommendation engine – buy brown shoes, likelihood to buy belt
3) Third option is HANA – with PAL in memory, connected to R
More to come…
ASUG Annual Conference has the following SAP Predictive sessions:
|Session ID||Title||Start Date|
|202||Predictive Analysis Roadmap||6/3/2014|
|203||Using Analytics to Help Win the US Presidency||6/3/2014|
|204||Predictive Analytics for Procurement Lead Time Forecasting at Lockheed Martin Space Systems Using SAP HANA, R, and the SAP Predictive Analysis Toolset||
Charles is presenting the Predictive Analysis Roadmap and co-presenting “Using Analytics to Help Win the US Presidency”.
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