10 Credits SPRING



Aims/Description: Many organisations are making use of data, analytics, and new technologies (e.g., Artificial Intelligence, cloud computing, Internet of Things, and Big Data) to drive digital transformation and become more 'data-driven'. Data science (and increasingly AI methods) can be applied in many ways within organisations and used for activities including business intelligence, data mining, predictive modelling and automation. A key use of data and analytics is to improve the outcomes (speed, accuracy, and relevance) for all types of decisions, from operational to strategic. The use of data science and more advanced techniques allows organisations to respond rapidly to changing requirements and contexts. In particular, the combination of predictive and prescriptive methods allows organisations to tackle complex problems, such as forecasting and simulating outcomes, that may assist with more informed and evidence-based decision making.  This module will help students to understand the organisational and business contexts in which data and data science can be used to support digital transformation. This includes the people, cultures, processes, and technologies that are needed to become an effective data-driven organisation. As well as considering the opportunities and benefits of using data and analytics, this module will also consider some of the common barriers faced by organisations in adopting such approaches. Students will also learn about the importance of data leadership to drive concrete actions and the need for a clear data strategy to guide and drive organisations to use and manage data effectively and achieve their specific business goals. The content in this module will be organised around three main themes:  - Organisations, the business context and the desire (and increasingly need) to be data-driven  - Building the capabilities of a data-driven organisation (i.e., what a data-driven organisation looks like) - The adoption of data and analytics, and developing maturity (i.e., how to create and grow as a data-driven organisation). 

Staff Contact: PARAMITA MONICA L
Teaching Methods: Lectures, Seminars, Independent Study
Assessment: Course work

Information on the department responsible for this unit (Information School):

Departmental Home Page
Teaching timetable

|

NOTE
The content of our courses is reviewed annually to make sure it's up-to-date and relevant. Individual modules are occasionally updated or withdrawn. This is in response to discoveries through our world-leading research; funding changes; professional accreditation requirements; student or employer feedback; outcomes of reviews; and variations in staff or student numbers. In the event of any change we'll consult and inform students in good time and take reasonable steps to minimise disruption.

URLs used in these pages are subject to year-on-year change. For this reason we recommend that you do not bookmark these pages or set them as favourites.

Teaching methods and assessment displayed on this page are indicative for 2024-25.

Western Bank, Sheffield, S10 2TN, UK