How an Open Analytics Platform became a Lifesaver

Description

Given the diverse talent and skill sets of today’s data scientist, now is the time for an analytic platform where you should not have to choose a single approach. To be viable in the open ecosystem of today’s economy and analytics, methods have to be open and integrated. Doug Liming explains where SAS fits into the open ecosystem, why you no longer have to choose between analytics languages like Python, R, or SAS, and how a single, unified open analytics architecture, empowered by Jupyter’s platform, can allow you to (literally) have it all. Doug details a case study involving one of the world’s largest health agencies. Dependent on donations and fundraising efforts, this agency suffered under the weight of data silos and data quality issues. Answering relevant business questions was both difficult and time-consuming. With help from Jupyter’s platform, SAS and an open analytics ecosystem, the company now makes data-driven decisions based on previously undetectable data patterns; as a result, employees spend less time generating reports, giving staff more time to work directly with patients, researchers, donors, and participants. Doug also explores how embracing Docker container technology and injecting Jupyter’s platform can help you provide a flexible infrastructure with all the tools and methods you need in one place. Join to learn how the strategic placement of Jupyter containers can push work inside Hadoop, minimizing data movement and time to insight, while maximizing analytic value.