Big data is out there, but it’s batch-oriented and decision-making is getting harder. To derive insights from data, a faster and better predictive model is required, with interactive search and analytics currently required. One company making waves in the industry is H2O, via its open source, in-memory machine learning and predictive analytics for big data.
H2O recently teamed with Cloudera, a company better equipped to help companies deploy an Enterprise Data Hub powered by Apache Hadoop.
Apache Hadoop is 100 percent open source, which enables distributed parallel processing of huge amounts of data across inexpensive, industry-standard servers without relying on expensive, proprietary hardware. No data is too big currently with Hadoop.
“H2O is pushing the boundaries of Hadoop and bringing data science to the masses by creating an easy to use, seamless experience for the user,” Tim Stevens, VP of business and corporate development at Cloudera, said in a statement.
“The joint solution expands the use cases for our customers by enabling customers to run predictive models across massive datasets at in-memory speeds,” Stevens added.
Leveraging Cloudera’s leadership and expertise in open source and big data infrastructure, H2O will enable enterprises to perform big data analysis in-memory at speeds up to 100 times due to its power to combine batch, interactive, and streaming jobs in the same application. Companies that use Cloudera’s Enterprise editions can now deploy H2O’s open source software on existing Hadoop clusters without the need for data transfers.
Moreover, Cloudera users can take advantage of having a seamless workflow and unified management of predictive analytics within Cloudera Manager and Cloudera Navigator.