February 24, 2017 | Written by: Matthew Wilson
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Billions of transactions in banking, transportation, retail, insurance and other industries take place in the private cloud every day. For many enterprises, the z System mainframe is the home for all that data.
For data scientists, it can be hard to keep up with all that activity and those vast swaths of data. So IBM has taken its core Watson machine learning technology and applied it to the z System, enabling data scientists to automate the creation, training and deployment of analytic models to understand their data more completely.
IBM Machine Learning supports any language, any popular machine learning framework and any transactional data type without the cost, latency and risk that comes with moving data off premises. It also includes cognitive automation to help data scientists choose the right algorithms by which to analyze and process their organization’s specific data stores.
One company that is evaluating the IBM Machine Learning technology is Argus Health, which hopes to help healthcare providers and patients navigate the increasingly complex healthcare landscape.
“Helping our health plan clients achieve the best clinical and financial outcomes by getting the best care delivered at the best price in the most appropriate place is the mission of Argus while focused on the vision of becoming preeminent in providing pharmacy and healthcare solutions,” said Marc Palmer, president of Argus Health.
For more, check out CIO Today‘s full article.