Innovation can and does occur in Bill Hewlett’s garage, but ultimately
you need a production-strength ISO 9001 factory. This is also true for
high performance data analysis projects.
R and python are great tools for research and for science projects -- in
the best sense of the word. Innovative approaches to get new analytic
outcomes are crucial to address the challenge of sense-making in a
complex data world.
But, once the lab project is proven to be a valuable analysis method,
we must make it performant, manageable, and make it scale to
work with data volumes that are meaningful for the mission, not just
with experimental sample data sets. In this talk we will learn how
SAP, the world’s largest Enterprise Software company, approaches
the problem of managing the execution of innovative machinelearning
and artificial intelligence algorithms to solve hard analytical
problems. We will discuss how to empower the data science team
at your organization to innovate with tools they are comfortable and
familiar with, yet deliver their innovation to the mission in a way that is
powerful and secure.
VP Software Solutions
SAP:NS2, National Security Services