It’s no secret that performing analytics where the data is created and lives is the best solution. That’s because analytics can be done natively on the mainframe rather than requiring users to export data, crunch the numbers, and then return them to the main system. But mainframes were originally built to be programmed in COBOL and assembly language – which aren’t exactly in everyone’s skill set in 2017. What if there was a way to use some of today’s most popular languages like Python to perform analytics on Big Iron?
As of today, there is.
Today Continuum Analytics, Rocket Software and IBM announced that we are joining forces to bring the modern open data science ecosystem of languages and technologies to z/OS to enable data science at the source of origin of data. With the industry focus on “data gravity,” IBM is working to evolve and extend z/OS and the momentum be built last year when the company enabled Spark on the platform to new types of analytics and machine learning through a partnership with Continuum Analytics and Rocket Software.
The ability to analyze data at source of origin optimizes the value of the insights derived, leverages modern skills including Python, Dask, Anaconda, NumPy, etc that create a unifying experience for data scientists at the same time providing differentiation through co-location with key business data resulting in real-time analytics with most current data.
Since working with IBM and the ecosystem of partners to enable open source on z/OS, the benefits to clients are becoming clear. This is just the beginning!
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