Big Data Insights Through Predictive Analytics, Open Standards and Cloud Computing

Grazed from SmartDataCollective. Author: Michael Zeller.

Organizations increasingly recognize the value that predictive analytics and big data offer to their business. The complexity of development, integration, and deployment of predictive solutions, however, is often considered cost-prohibitive for many projects. In light of mature open source solutions, open standards, and SOA principles we propose an agile model development life cycle that quickly leverages predictive analytics in operational environments.

Starting with data analysis and model development, you can effectively use the Predictive Model Markup Language (PMML) standard, to move complex decision models from the scientist’s desktop into a scalable production environment hosted in the cloud (Amazon EC2 and IBM SmartCloud Enterprise)…

Expressing Models in PMML

PMML is an XML-based language used to define predictive models. It was specified by the Data Mining Group, an independent group of leading technology companies including Zementis. By providing a uniform standard to represent such models, PMML allows for the exchange of predictive solutions between different applications and various vendors.

Open source PMML-compliant statistical tools such as R, KNIME, and RapidMiner can be used to develop data mining models based on historical data. Once models are exported into a PMML file, they can then be imported into an operational decision platform and be ready for production use in a matter of minutes…

Read more from the source @ http://smartdatacollective.com/michaelzeller/78941/big-data-insights-through-predictive-analytics-open-standards-and-cloud-computin