Faculty
Isabel Cristina Flores Vieira e Silva
Objectives
At the end of the course students will be able to: Recognize the usefulness of making decisions using data | Be aware of ethical issues, risks and the need for transparency in the use of data | Know where and how to collect information, organize a database, know how to ask the right questions and interpret information from: descriptive analyses, application of algorithms and induction, understand processes of relationship between variables and concepts of event probability | Knowing how to look for data produced by others, knowing how to order useful studies | Linking data and decision - designing management measures and processes and anticipating what to expect through the analysis of predictive models.
Program
The motivations for using data| Ethics in the use of data | The New World of Data Everywhere | Some Basic Analysis Tools | Evaluate and decide based on research data produced by others | Knowing how to ask for data |From data to decision causes and consequences.
Evaluation process
The process is online with delivery of concepts part - videos, ebooks and reading of articles and other materials. All subunits will have moments of interactivity and work developed by the student.
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Elearning course with an evaluation process that will include: Discussion forums (15%)| delivery of work and analysis of case studies (30%)| answer to questions (15%) and a final work of application to context (40%). Each subunit will require the demonstration of knowledge acquisition.
Bibliography
Mandatory Bibliography
From evidence-based policy to the good governance of evidence,
OECD (2019), The Path to Becoming a Data-Driven Public Sector, OECD Digital Government Studies, OECD Publishing, Paris, https://doi.org/10.1787/059814a7-en. | Broomfield, H. Reutter, L (2021) Towards a Data-Driven Public Adminsitrtion: An Empirical Analysis of Nascent Phase Implementation, Scandinavian Journal of Public Administration 25(2):3-97 | Brown, D.C.G. and Toze, S. (2017), Information governance in digitized public administration. Can Public Admin, 60: 581-604. https://doi.org/10.1111/capa.12227 | Mittal, P. (2020). Big data and analytics: a data management perspective in public administration. International Journal of Big Data Management, 1(1), 1. https://doi.org/10.1504/ijbdm.2020.10032871 | Parkhurst, J. (2017) The Politics of Evidence, Routledge
Optional Bibliography
https://joinup.ec.europa.eu/collection/study-data-analytics-member-states-and-citizens | https://www.ttec.com/articles/data-driven-decision-making-work-public-sector | https://www.govx.digital/data/essential-guide-data-driven-government | https://onlinemasters.ohio.edu/blog/why-learning-data-analysis-is-essential-for-public-administrators/