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H2O brings in-memory predictive analytics to Hadoop

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Soma Tah
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MOUNTAIN VIEW, USA: H2O, the open source in-memory machine learning and predictive analytics company for big data, announced that its flagship H2O product is available on the Intel Distribution for Apache Hadoop (Intel Distribution).

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Companies that use the Intel Distribution are now able to use open source H2O to run advanced algorithms on existing data stored in Hadoop clusters with no need for data transfers. By combining the power of H2O's highly predictive algorithms with the high performance Intel Distribution, organizations can discover valuable insights up to 100x faster than alternatives.

The key to H2O's interactive performance is its fast in-memory parallel processing. Cache oblivious implementations of algorithms over columnar compressed data delivers distributed machine learning algorithms at blazing speeds.

"Big data is transformative for enterprises," said SriSatish Ambati, co-founder and CEO of H2O. "By offering the H2O product with the Intel Distribution for Apache Hadoop, customers will achieve near-real time predictions and nano-second scoring to prevent credit card fraud, customer churn and better sales predictions."

H2O delivers parallel and distributed advanced algorithms on big data at speeds up to 100x faster than other predictive analytics providers and is easy to install and deploy in place on big Hadoop clusters. With a simple click, data models can be expressed into scoring engines ready for low latency production environments.