IBM has awarded a $20,000 grant to a team consisting of Maria Liakata (Computer Science Warwick), Emma Uprichard (Q-Step Centre Warwick) and Arne Strauss (Warwick Business School) to develop a three day workshop on ethics of big data and data linkage.

The IBM Faculty Awards is a competitive worldwide program intended to:

• Foster collaboration between researchers at leading universities worldwide and those in IBM research, development and services organizations
• Promote courseware and curriculum innovation to stimulate growth in disciplines and geographies that are strategic to IBM.

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In a joint effort between IBM volunteers and members of the Operational Research & Management Science (ORMS) Group at the triple-accredited Warwick Business School (WBS), we have embarked on the development of an entirely new module “Analytics in Practice” on the technology needed for big data analytics.

“Analytics in Practice” will become a core module for the M.Sc. in Business Analytics & Consulting program at WBS and will complement the methodological training that WBS is currently offering in that it will impart knowledge on business intelligence and on the IBM software tools that are specifically tailored to big data applications such as BigSheets (front end for Apache Hadoop), Cognos or SPSS Modeler.

Links between IBM and WBS have traditionally been tight; in fact, Warwick was the first European IBM partner university, established at the time by Ian Nussey and IBM Fellow Tony Temple, who is still a Board member of WBS. E.g., a distance-learning MBA program was devised exclusively for IBM staff which has 100 students per annum. WBS is keen to collaborate with industry in both research and teaching; we aim for about 10% of each M.Sc. program to be taught by practitioners.

“Analytics in Practice” will aim to familiarize students with practical aspects of big data analytics such as the types of data, their structure and the data lifecycle. Data sources, extraction, cleansing and manipulation as well as dashboarding and visualization are further business intelligence topics that will be covered. Students will be exposed to real-world analytical applications via case studies in IBM’s focus areas like smarter cities and improving business performance, and they will learn about technical challenges.

The module’s content is central knowledge required for job roles like Data Scientists, Business Analysts and Visual Analysts, and we expect that the use of Big Data software tools such as Cognos, SPSS and Big Insights on realistic data sets will increase the students’ real-world awareness and further improve their employability.

As well as focusing on current IBM software offerings, the course will look to analyze emerging trends in the field and look specifically at the new generation of knowledge and learning systems that are being built from a foundation of unstructured data, predictive technology and analytical capability such as IBM Watson. Students as well as understanding the underlying components of such a system will be challenged to think about new fields where such systems can be deployed and to explore the business, ethical and process challenges that such systems introduce.