Data Visualization

Justification
The graduate in Data Science and Artificial Intelligence designs and develops software applications that collect and process data and visualize the information obtained as a result of this analysis. These visualizations are designed so that a person can establish a dialogue with them and obtain valuable information efficiently and effectively. To this end, it is necessary that the person who designs them has basic knowledge of the types of visualization, the different graphics and when to use them, as well as the tools to generate them.

This course contributes to the graduate's profile by giving him/her the necessary tools to design, develop and evaluate data visualizations that effectively convey valuable information to people.

This course contributes to the development of the following specific competencies of the degree:
CE-CD-03. Apply the principles of visual organization of information and information representation to the design of solutions based on visual information analytics.

This course contributes to the development of the following generic competencies of the degree:
CG2 - Express with clarity and opportunity one's ideas, knowledge and feelings through words and visual representations, adapting to the particular contexts and terminology used in the business environment, to achieve the audience understanding.

Subject competencies
CE-CD-03. Apply the principles of visual organization of information and information representation to the design of solutions based on visual information analytics.

This competency is divided into the following specific competencies (SC):

SC1. Design basic quality data visualizations.
SC2. Evaluate the quality of data visualizations and identify the improvements needed for a good data representation.
SC3. Based on complex data, use advanced data visualization techniques to present information to the user.
SC4. Analyze, design and implement applications that provide continuous visualizations of data flows.

CG2 - Express with clarity and opportunity one's ideas, knowledge and feelings through words and visual representations, adapting to the particular contexts and terminologies used in the business environment, in order to achieve audience understanding.

Course content
1. Introduction and History of Data Visualization.
2. Planning a visualization.
3. Data story types and design principles.
4. Types of charts and how to choose them. Bad design and lying with statistics. Visual perspectives: relationships and structures. Visual perception and information design for the mind.
6. Visualization with temporal and geographical components.
7. Interactive and animated visualizations.
8. Dashboards design and implementation.

EVALUATION SYSTEM

Evaluation techniques

Continuous evaluation (CE): periodic evaluation of the "Student's Portfolio" that collects the work and activities carried out during the course.

Final evauation (FE): a project that integrates all concepts and competencies developed during the course.

Evaluation by competencies

CE-CD-03 represents 90% of the evaluation and CG2 represents 10% of the evaluation.