Warwick Business School teams with IBM and SAS on big data course

Warwick Business School has teamed up IBM and business intelligence specialist SAS to teach students how to mine big data.


Warwick Business School has teamed up IBM and business intelligence specialist SAS to teach students how to mine big data.

Students taking the MSc Business Analytics course at Warwick Business School can now learn the latest quantitative consultancy techniques around big data.

Working with Warwick Business School’s Operational Research and Management Science (ORMS) group, IBM has helped put together Analytics in Practice, a module that will explore the technology needed for big data analytics, by using tools such as BigSheets (front end for Apache Hadoop), Cognos and SPSS Modeller.

While with SAS the ORMS group has produced Text Analytics where students will learn predictive modelling techniques using SAS software, model assessment and implementation, report writing and learn to use the SAS Text Miner tool and applications.

Assistant professor of operational research Arne Strauss said, "Data mining skills are something that more and more companies are looking for from graduates and these two modules offer students cutting edge technology to learn the latest techniques.”

She said the IBM module would expose students to real life analytical applications via case studies in IBM’s focus areas, such as smarter cities and improving business performance.

“We are equally pleased to be working with SAS in producing the Text Analytics module. SAS skills have never been in greater demand in the UK and are heavily used in the financial, retail and government sectors," said Strauss.

The SAS module will teach students how to sift through data by using sophisticated linguistic rules and statistical methods to evaluate text, and discover topics and patterns within entire document collections.

By the end of the module students will have learned how to uncover underlying themes or concepts contained in large document collections, automatically group documents into topical clusters, classify documents into pre-defined categories and integrate text data with structured data to enrich predictive modelling.

There will be an open day for potential entrants to the course on Wednesday 19 March.

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