Spark on z/OS and Jupyter: fast, flexible analysis of mainframe data

Many enterprises are faced with the need to expand data processing access to users without impacting mission-critical transactional application environments. The trending approach to this problem is to move┬áthe data from these systems of record to a data warehouse. Moving data-at-rest to a mirrored data repository for analytics can yield costly side-effects such as expensive migration workloads, data concurrency and […]

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Unleashing Exploration on Enterprise Data

Enterprise customers have huge investments in transactional data systems, yet they struggle to provide their users with flexible and timely exploratory access to this data. One solution to this problem is to empower these users with the ability to use Jupyter Notebooks and Apache Spark running natively on z/OS to federate analytics across business critical data as well as external […]

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