BBBT - IBM - 2017
Event Details
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Topic:
Enabling the Coders and the Clickers in Data Science
Summary:
IBM believes data science is a team sport. That means you have to enable the coders as well as the clickers so they can collaborate on the same project, sharing data, results and analytic assets. IBM built Data Science Experience (DSX) as the core platform on which a data scientist can work but also collaborate with others on the data science team. Tools like SPSS Modeler, SPSS Statistics and Watson Explorer can integrate with DSX. In addition, DSX supports new machine learning capabilities that allow continuous intelligence and model management, making the implementation of discoveries easy. All this adds up to enabling everyone to discover more and to build more intelligence into their business.
Presenter(s):
Nancy Hensley — Director, Offering Management, IBM Analytics
Nancy’s responsibilities for IBM Analytics include digital strategy, ecosystem, and portfolio strategy, and she is part owner of IBM’s data science portfolio.
Armand Ruiz — Lead Offering Manager, IBM Data Science Experience, IBM Watson Machine Learning
Armand’s responsibilities include offering strategy, some development, demos and outreach around IBM’s work on data science and machine learning.
Ted Fischer — Senior Offering Manager, IBM SPSS Modeler/Data Science, IBM Analytics
Ted’s responsibilities include offering management, offering strategy, demos and outreach for IBM SPSS Modeler, IBM SPSS Statistics and IBM’s data science work.
Tanmay Sinha — Senior Offering Manager, IBM Watson Explorer
Tanmay’s responsibilities include offering management, offering strategy, demos and outreach for IBM Watson Explorer.
Company Profile:
For more than a century IBM has been dedicated to every client’s success and to creating innovations that matter for the world. IBM Analytics offers a complete portfolio of big data and analytics solutions to fuel cognitive businesses. IBM solutions enable organizations to engage with data to answer the toughest business questions, uncover patterns and pursue breakthough ideas.