ADAPA for SAP
HANA provides a simple plug-and-play platform to deploy the most complex
predictive models and execute them in real-time, even in the context of Big
Data.
In joining the
SAP HANA Startup Focus program, Zementis set out to address two key challenges
related to the operational deployment of predictive analytics: Agile deployment and scalable execution.
Transactional
data has for years pushed the boundaries of predictive analytics. The financial
industry, for example, has been using transactional data to detect fraud and
abuse for decades with complex custom solutions. Real-time scoring is paramount
for companies to be able to predict and prevent fraudulent activity before it
actually happens. Likewise, the Internet
of Things (IoT) demands effective processing of sensor data to employ predictive
maintenance for detecting issues before they turn into device failures.
To solve these
challenges, Zementis combined its ADAPA predictive analytics scoring engine
with SAP HANA in a true plug-and-play platform which is universally applicable across
all industries. ADAPA to serve scoring
requests and execute predictive models, HANA to offload complex model
preprocessing and computation of aggregates.
In this scenario,
real-time execution critically depends on HANA serving complex data lookups and
aggregate profile computation in a few milliseconds. In a high-volume environment, such aggregates
or lookups may have to be computed over millions of transactions.
ADAPA provides
scalable real-time scoring of the core model, plus agility for model deployment
through the Predictive Model Markup Language (PMML) industry standard. Clients are able to instantly deploy existing
predictive models from various data mining tools. For example, you can take a complex
predictive model from SAS Enterprise Miner, export it in PMML format and simply
make it available for real-time scoring in ADAPA for SAP HANA. The same process, of course, applies to most commercial
tools, e.g. SAP Predictive Analysis, KXEN, IBM SPSS, as well as open source tools
like R and KNIME.
The unique aspect
of the Zementis / SAP platform is that it combines the benefits of an open
standard for predictive analytics with the power of in-memory computing.
For more product
details, please see http://zementis.com/saphana.htm
