Each day, a multitude of transactions take place in various industries, including insurance, banking, retail, healthcare, transportation and government firms in the private cloud. Most of this global enterprise data is housed in the IBM z System Mainframe.
To make management of this huge amount of data and associated activities easier for the data scientists, IBM has applied its Watson’s core machine learning technology to the z System mainframe. This will enable data scientists to use automation for creating, training and deploying operational analytic models that will provide support for any Machine Learning Framework (like H2O or Apache SparkML), any language (like Python or Scala) and any data type.
With IBM Machine Learning, there will be no additional cost, risk or latency associated with shifting data off systems for analyzing as is there with conventional ETL processes. Cognitive automation associated with IBM Machine Learning will help data scientists in selecting the right data algorithm for quickly analyzing and processing their enterprise’s data stores.
Machine Learning represents a new frontier in analytics. IBM Machine Learning leverages IBM’s core Watson technologies to enhance the rate of adoption of machine learning where corporate data houses. IBM Machine Learning is available firstly on z/OS and will soon be available for other platforms like IBM POWER Systems.
For more information on IBM Machine Learning, visit: https://ibm.biz/machinelearning.