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Predictive Analytics standards—R, Hadoop and PMML

"Predictive Analytics standards—R, Hadoop and PMML"

Standards in Predictive Analytics

White Paper: Decision Management Solution

Standards play a central role in creating an ecosystem that supports current and future needs for broad, real-time use of predictive analytics in an era of Big Data.
Just a few years ago it was common to develop a predictive analytic model using a single proprietary tool against a sample of structured data. This would then be applied in batch, storing scores for future use in a database or data warehouse. Recently this model has been disrupted.
There is a move to real-time scoring, calculating the value of predictive analytic models when they are needed rather than looking for them in a database. At the same time the variety of model execution platforms has expanded with in-database execution, columnar and in-memory databases as well as MapReduce-based execution becoming increasingly common.

Standards in Predictive Analytics
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What is

What is Big Data ?

Big data is the act of collecting huge amount of enterprise data that can be used for future analysis. Big data helps all kind of industry data to grow securely that includes government, banking, retail, education and healthcare. Big data stores all kind of data including structured, unstructured and semi structured data, which contains valuable information about core functions of an enterprise such as finance, marketing, procurement.

What is Analytics ?

Analytics is the process of obtaining an optimal and realistic decision based on examining existing data, typically large sets of business data, with the aid of mathematics, statistics, specialized systems and software. In the last few years use of analytical methods to extract useful insights from data have gained immediate importance and has helped several companies improve their business performances.

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