Zementis’ Standards-Based Predictive Analytics Empowers Big Data Scoring
Customers want to make more rapid, data-driven decisions but historically this has been challenging in the era of Big Data. Predictive analytics, machine learning and statistical algorithms are at the leading edge of where enterprises can unlock the value hidden in their data to deliver timely insights for intelligent decisions.
Zementis is a new Hortonworks Technology Partner offering a standards-based predictive analytics scoring engine for Hortonworks Data Platform (HDP) and existing data repositories as part of the Modern Data Architecture (MDA). Here, Zementis’ Alliance Manager, Henry Huang, describes the scoring solution with HDP and other ecosystem partners Teradata, SAP and Datameer.
The Zementis Universal PMML Plug-in (UPPI), an in-database scoring engine for Hadoop and data warehouse solutions, provides a highly scalable framework to deploy, execute and act on sophisticated predictive analytics models based on the PMML standard. With PMML, the Predictive Model Markup Language, models built in most commercial or open source data mining tools, such as SAP KXEN or R, can now instantly be deployed in the operational IT environment. Zementis solutions reduce cost and complexity of predictive analytics, accelerates time-to-market for intelligent business decisions and enables automation for real-time scoring or big data processing.
Zementis partners with Hortonworks to deliver a cross-industry platform that is applicable to the most complex scoring solutions.
- Highly scalable scoring for the Hortonworks Data Platform: The Zementis Universal PMML Plug-in (UPPI) for Hive embeds standards-based predictive analytics into the extremely scalable and reliable Hadoop framework (HDP). This enables data-driven enterprises to capture business value from Big Data by turning into actionable insights for smart decisions.
Extending its standards-based capabilities even further into the Hortonworks ecosystem, Zementis also partners with Hortonworks’ partners Teradata, SAP and Datameer. This enables prediction models to seamlessly travel between HDP and other ecosystem partner solutions, and allows scoring to take place in the most applicable environment.
- Massively parallel scoring for Teradata/Aster: The Zementis Universal PMML Plug-in (UPPI) for Teradata/Aster leverages the high-performance data warehouse with its massively parallel processing capabilities for rapid execution of standards-based predictive analytics. Since models and data reside together, scores and prediction flow achieves enterprise-grade performance and scalability while eliminating data movement.
- Real-time scoring for SAP HANA: The solution combines the advantages of Zementis ADAPA, a standards-based, real-time scoring engine, with the ultra-fast, in-memory aggregation capabilities of SAP HANA, driving on the fly decisions in the context of millions of transactions and customer interactions.
- UPPI for Datameer delivers standards-based execution of predictive analytics on a massive parallel scale. This solution combines the Zementis plug-in for execution of predictive models with the power and scale of Datameer, an end-to-end BI solution that includes data source integration, an analytics engine, visualization and dash-boarding.