Business Analytics and Data Culture

No prior knowledge is required. 

The Business Analytics Curricular Unit allows students to gain knowledge, learn to manage and develop the ability to propose Data Analytics solutions, in particular Data Visualization, aimed at any type of organization, considering business rules.
Students will use Business Analytics tools for development and artifacts (dashboards) for decision making. Students will have to make decisions regarding the data to be used and the processes necessary to guarantee the quality of the data, they will understand which are the fundamental and relevant indicators for decision-making in an organizational context and will propose the most appropriate way to present and communicate information in a transparent way. understandable by the intended audience.
Few (2019) states that “we are not yet in the Information Age, but in the data age” and, given the multitude of data available to facilitate the decision-making process, students will have an advantage if they are able to, in their companies, propose more efficient and effective solutions for the presentation of information.

It is intended that students become aware of the various players in this area, whether software houses and solutions available on the market, organizations that promote the discussion of the topic (International Institute of Business Analysis, Canada), or researchers and studies on the topics under discussion. .

Thus, the methodology followed is “Problem-based Learning” and “Project-based learning”: students will be motivated to solve problems and analyze scenarios, as well as prepare a data analysis project with different phases and deliverables.

The challenges of data analysis are, today, very focused on promoting a true “data culture” in organizations, in addition to a deep knowledge of the business in which each company/organization operates, which, acting in harmony, allows the application of effective data-driven decision making policies.

Tools for data visualization, namely from a perspective of self-service use, on cloud platforms, are now the rule: democratic access to data is also a fundamental topic of discussion.

In the Business Analytics and Data Culture UC (BACD), special emphasis is given to the themes, applications and potential of Business Analytics and the challenges related to data-based decision-making, which must be overcome so that a true data culture can emerge, namely: data quality, data transformation processes, real-time updating and visualization and collaborative use of data and generated output.

GOALS

The objectives of this UC are the following:

– get to know applications and capabilities of Business Analytics

– identify the challenges related to data-based decision-making and the implementation of a data culture in organizations

– master the processes of data transformation, real-time updating and visualization, and collaborative use of data

– promote a decision-making culture based on data and the critical spirit associated with the generated outputs.

SKILLS

– advise organizations on data-driven decision-making and moving to a data culture

– knowing how to overcome the challenges related to data-based decision-making and the implementation of a data culture in organizations

– produce dashboards using Power BI, from raw data

– Introduce data visualization solutions that promote a data-driven decision-making culture.

1 –Business Analytics and Data Culture fundamentals
1.1 Data Analytics Life Cycle
1.2 Data sources
1.3 Data transformation
1.4 Data Quality
1.5 Digital Curation
1.6 Ethical issues and GDPR
2 – Data visualization
2.1 Guidelines for Data visualization
2.2 Tools for Data visualization
2.3 Data visualization process: planning, monitoring, and discussing

NAO

Fundamental references:

– Laursen, G. H., & Thorlund, J. (2016). Business analytics for managers: Taking business intelligence beyond reporting.John Wiley & Sons.
– Few, S. (2019), The Data Loom: Weaving Understanding by Thinking Critically and Scientifically with Data, AnalyticsPress.
– Few, S. (2019), Now You See It: Simple Visualization Techniques for Quantitative Analysis, Analytics Press.
– Pochiraju, B., & Seshadri, S. (Eds.). (2019). Essentials of Business Analytics: An Introduction to the Methodology and Its Applications (Vol. 264). Springer.

Complementary references: 

Aparicio, M., & Costa, C. J. (2015). Data visualization. Communication design quarterly review, 3(1), 7-11.
M. Y. Santos e I. Ramos, Business Intelligence – da Informação ao Conhecimento – 3.a edição Atualizada, Editora FCA,2017. ISBN: 978-972-722-880.
Schniederjans, M. J., Schniederjans, D. G., & Starkey, C. M. (2014). Business analytics principles, concepts, and applications with SAS: what, why, and how. Pearson Education.