Data Science for Decision-Makers

Module description

Decision-makers have an array of tools at their disposal for measuring performance, managing organisational risk and quantifying value. Where once quantitative analysis assisted decision-making by enriching organisational systems and enabling valuable data to be derived within the operational arena; boardroom business is increasingly taken-up with a quest for maximising competitive potential using information owned by the firm in question. In the first part of the module, you will be introduced to some of the key techniques used by data scientists in quantifying and synthesizing data arising from multiple data points, including those logged by machines and sensors as centralised data and those held on a new generation of local storage devises, run in the home and via computer clouds. Such developments make Grieve’s and Vicker’s ‘digital twinning,’ hypothesis a plausible reality. We will then consider how these techniques will alter digital business models, including those that already make use of prosumer dynamics and/or decentralised devises.

Full module specification

Module title:Data Science for Decision-Makers
Module code:BEMM078
Module level:M
Academic year:2020/1
Module lecturers:
Module credit:15
ECTS value:
Pre-requisites:
Co-requisites:
Duration of module: