Agenda

3:30 - 4:00 p.m
Registration and welcome coffee

4:00 - 4:15 p.m
Embrace and Extend: Integration with Open Source Analytics
Dr. Mark Wolff, Ph.D., Principal Industry Consultant, Chief Health Analytics Strategist, SAS

Nearly 40% of existing SAS customers use open source software in conjunction with SAS for their analytics platform.
Many organizations balance open source solutions with commercial software to meet the requirements for statistical analysis both within their organizations and externally with regulatory bodies. While open source analytic tools offer a robust online community, and extensive array of algorithms, packaged analytics software companies, most notably SAS, offer the performance, scalability, governance, and support organizations require for production and operational analytics. For many organizations open source and SAS are quickly becoming a complementary partnership. Choosing the best analytics approach for a particular task, considering the source, volume, and sensitivity of data, will help organizations ensure they maximize returns from both analytics approaches while making the most of their existing SAS investment.​
4:15 - 4:45 p.m

Prototyping in R, Operationalisation in SAS
Prof. Gerold R. Baudinot, Director of Department Computer Science, Electrical Engineering and Mechatronis,
ZHAW School of Engineering

Google Trends and other IT fever charts rate Data Science among the most rapidly emerging and promising fields that expand around computer science. Although Data Science draws on content from established fields like artificial intelligence, statistics, databases, visualization and many more, industry is demanding for trained data scientists that no one seems able to deliver. This is due to the pace at which the field has expanded and the corresponding lack of curricula; the unique skill set, which is inherently multi-disciplinary; and the translation work (from the US web economy to other ecosystems) necessary to realize the recognized world-wide potential of applying analytics to all sorts of data. Moreover the operationalization of the Data Scientists work such as Dataproducts still seems still to be a hard task. ICT departements main obligation is to engineer and manage their ICT as a highly efficient, resilient and reliable Service. Their means to achive these demanding goals is on one hand a highly standardized architecture and on the other hand highly structured processes. For Data Scientist with their special products such “bricks and mortar” culture is often difficult to overcome when they would like to put the code into production.

In this contribution we draw from our experiences in establishing an inter-disciplinary Data Science lab in order to highlight the challenges and potential remedies for Data Science in Europe. We discuss our role as academia in the light of the potential societal/economic impact as well as the challenges in organizational leadership tied to such inter-disciplinary work.

4:45 - 5:15 p.m

How can SAS and R co-exist at Nestlé?
Laura Gosoniu,  Ph.D, Biostatistician Clinical Development Unit,
Nestlé Research Center

Nestlé Clinical Development Unit is responsible for the design and execution of all corporate clinical trials worldwide. The Biostatistics group supports the planning, execution and finalization phases of the studies by providing appropriate statistical expertise. Until recently, the group had a heterogeneous way of working in both R and SAS, resulting in a non-standardized way of presenting the results. In order to absorb the peaks in the group’s workload, an outsourcing strategy was put in place. In addition, more and more of our studies are going through regulatory submission; therefore we need to make sure that the requirements for statistical analysis with external regulatory bodies are met. For all these reasons, the Biostatistics team decided to make SAS the homogeneous working environment for operational activities. To create reports that include text, tables and figures (similar to Sweave or knitr), the team developed a SAS based tool which have these features and produces editable and polished reports. To nurture the collaboration with both academic institutions and industry, the group will maintain expertise in both statistical environments.

 

5:15 - 5:45 p.m
Illustration and live demo of the different ways to combine SAS and R
Carmelo Iantosca, Practice Leader Analytics, Senior Solution Specialist Analytics, SAS
5:45 p.m
Exchange experience and networking
When

Thursday, December 3rd 2015

Where

SAS Institute AG
Richtistrasse 11
CH – 8304 Wallisellen
www.sas.com/ch

 

Contact

We remain at your entire disposal for
any information you may require.

Isabelle Wirth
isabelle.wirth@sas.com
+41 44 805 74 74

 

More information

Open source intelligence


The event is free of charge

 

 

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