The Expert Group of the Data+Service alliance, “Software & Tools”, is meeting on the 31st of March 2017 at ZHAW Lagerstrasse Zurich. The first meeting of the expert group was on January 20th 2017, where the group officially kicked-off and the activities were planned.
Data Science has recently gained significant attention both in academia and industry. Especially in the areas of big data and machine learning the software and tools landscape is changing rapidly. This makes it very difficult for companies to keep up to date and choose the right time to embark on new technologies. Unlike universities that typically experiment with the latest features, companies are often more conservative due to legacy software.
The goal of this expert group is to provide a technology radar for software and tools and to discuss new trends as well as best practices. Similar to Gartner’s Magic Quadrant, the idea is to become the major reference to Data and Service Science related technology insights.
The expert group is lead by Kurt Stockinger (ZHAW), Philippe Cudre-Mauroux (eXascale Infolab) and Christian Gügi (Scigility).
The expert group activities are accessible only to the members of the alliance. If you are a member already and would like to join this expert group, please get in touch directly with the group leaders. If you are not a member of the alliance, please get in touch with us to discuss the different membership possibilities.
For the upcoming workshop following 2 talks are scheduled which will be followed by a round of discussion.
Text Mining: Open Source versus Proprietary Software – Mirco Rossi, Mobiliar
Many data science projects at Mobiliar are in the domain of text mining. The main goal is to unleash the information of unstructured text data. Methods like text clustering, text classification or named entity extraction are used, which are implemented both in open source and proprietary software. This presentation should open the discussion to share the experience of the group members in “open source versus proprietary software” in the text mining or related domains.
Data science architecture at SwissRe – Lukasz Lewandowski, SwissRe
With the introduction of a data science workplace Swiss Re embraced a bi-modal approach to support practical data science operations in an enterprise IT context. A light-weight release model for analytics apps and microservices embeds these activities in a larger software development lifecycle of the company, and allows for effective prototyping and roll out of text mining and predictive solutions.