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Digital Analytics

Code: 104753 ECTS Credits: 6
Degree Type Year Semester
2503873 Interactive Communication OT 4 1


Adrian Padilla Molina

Use of Languages

Principal working language:
catalan (cat)
Some groups entirely in English:
Some groups entirely in Catalan:
Some groups entirely in Spanish:


Adrian Padilla Molina


To be able to take this subject it is necessary to have basic knowledge of the English language to face the reading of the bibliography.

Objectives and Contextualisation

Learn data collection techniques for preparing reports based on information obtained from the Internet in order to optimize processes.

Measurement and data collection systems and web analytics tools will also be delved into.

Social media analytics and Mobile analytics will play a prominent role, as well as measurement strategies


  • Act with ethical responsibility and respect for fundamental rights and duties, diversity and democratic values.
  • Act within one's own area of knowledge, evaluating sex/gender-based inequalities.
  • Identify the characteristics of information systems from both a conceptual and a practical perspective.
  • Introduce changes in the methods and processes of the field of knowledge to provide innovative responses to the needs and demands of society.
  • Manage time efficiently and plan for short-, medium- and long-term tasks.
  • Plan, implement, analyse and evaluate social-media marketing campaigns and implement automation systems in management.
  • Search for, select and rank any type of source and document that is useful for creating messages, academic papers, presentations, etc.
  • Students must be capable of applying their knowledge to their work or vocation in a professional way and they should have building arguments and problem resolution skills within their area of study.
  • Students must be capable of collecting and interpreting relevant data (usually within their area of study) in order to make statements that reflect social, scientific or ethical relevant issues.
  • Students must have and understand knowledge of an area of study built on the basis of general secondary education, and while it relies on some advanced textbooks it also includes some aspects coming from the forefront of its field of study.
  • Take account of social, economic and environmental impacts when operating within one's own area of knowledge.

Learning Outcomes

  1. Analyse a situation and identify its points for improvement.
  2. Analyse reports on internet and mobile data.
  3. Analyse the sex-/gender-based inequalities and gender bias in one's own area of knowledge.
  4. Communicate using language that is not sexist or discriminatory.
  5. Consider how gender stereotypes and roles impinge on the exercise of the profession.
  6. Create measurement strategies.
  7. Critically analyse the principles, values and procedures that govern the exercise of the profession.
  8. Cross-check information to establish its veracity, using evaluation criteria.
  9. Distinguish the salient features in all types of documents within the subject.
  10. Evaluate the impact of problems, prejudices and discrimination that could be included in actions and projects in the short or medium term in relation to certain people or groups.
  11. Identify data-collection systems.
  12. Identify the social, economic and environmental implications of academic and professional activities within one's own area of knowledge.
  13. Interpret big data in websites and applications.
  14. Interpret the results of content creation based on scientific thought.
  15. Plan and conduct academic studies in the field of digital analytics.
  16. Propose new methods or well-founded alternative solutions.
  17. Propose new ways to measure the success or failure of the implementation of innovative proposals or ideas.
  18. Propose projects and actions that are in accordance with the principles of ethical responsibility and respect for fundamental rights and obligations, diversity and democratic values.
  19. Propose projects and actions that incorporate the gender perspective.
  20. Propose viable projects and actions to boost social, economic and environmental benefits.
  21. Recognise the different tools of web analytics.
  22. Submit course assignments on time, showing the individual and/or group planning involved.
  23. Understand and apply the metrics of web analytics.
  24. Weigh up the risks and opportunities of both one's own and other people's proposals for improvement.


  • Introduction to Analytics
  • Web Analytics: Google Analytics, Google DataStudio, measurement paradigms.
  • Digital Analytics: Analytics applied to social networks and digital platforms.


The acquisition of knowledge will be done through various methodological procedures that include different types of activities, grouped into: master classes, internships and seminars.

In the theoretical sessions, the contents of the program will be presented, thus providing the necessary elements to carry out the practical exercises in the laboratories.

As for the practices, they will be used to apply in real cases the knowledge acquired in the theoretical sessions. The seminars encourage critical reflection and debate on the analysis of real cases and models.

The detailed calendar and content of the different sessions will be presented on the day of presentation of the subject and will also be posted on the virtual campus where students can find the detailed description of the exercises and practices, as well as the various teaching materials and any information necessary for the proper follow-up of the subject.

In the case of a change in teaching modality for health reasons, the teaching staff will inform of the changes that will take place in the programming of the subject and the teaching methodologies.

Note: 15 minutes of a class will be reserved, within the calendar established by the center / degree, for students to complete the surveys for evaluating the performance of teachers and evaluating the subject / module.

Annotation: Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.

Annotation: Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.


Title Hours ECTS Learning Outcomes
Type: Directed      
Laboratory practices 12 0.48 2, 23, 21, 11, 13, 14, 15, 22
Master classes with ICT support 15 0.6 7, 1, 8, 9, 12, 24, 16, 17, 18, 20, 10
Seminars 21 0.84 7, 3, 1, 4, 8, 9, 12, 24, 22, 16, 17, 18, 19, 20, 5, 10
Type: Supervised      
Theoric exam 3 0.12 7, 23, 21, 11, 13, 18, 10
Type: Autonomous      
Study: Reading and synthesis of scientific documents 54 2.16 7, 2, 1, 8, 6, 9, 11, 12, 13, 14, 10
Tutorials (individual or group face-to-face activity aimed at solving learning problems) 12 0.48 7, 2, 3, 4, 6, 13, 14, 15, 18, 19, 5, 10


The competencies of this subject are evaluated with different activities:
- Theoretical test (40% of the final grade)
- Delivery of group work  (40% of the final grade)
- Delivery of individual workss (20% of the final mark)
The final grade will be the sum of the score obtained in each of these parts.
It is essential to take the three assessment tests to pass the subject.
The weighting of the three evaluable parts will be done, even if one of them is suspended. But the weighting will not be performed if two are suspended.
The evaluation system of this subject corresponds to continuous evaluation.
Students will be entitled to retake the subject only if they have been assessed in the set of activities. Only suspended laboratory practices and the written test may be recovered. Therefore, all activities not submitted are excluded from recovery. Seminars are not recoverable and therefore are not re-evaluable.
The maximum mark in the recovered laboratory practices will be 5 out of 10.
The mark obtained in the recovery of the written test will be the final mark of this section, regardless of whether it is better or worse than the first test taken.
Attendance: Attendance at seminar classes and laboratory practices is mandatory. The unjustified absence of the students in these sessions entails a "not presented" in the note of the seminar or specific practice, and therefore will not be recoverable.
In the event that the student performs any irregularity that may lead to a significant variation of an evaluation act, this evaluation act will be graded with 0, regardless of the disciplinary process that could be instructed. In the event, that several irregularities occur in the evaluation acts of the samesubject, the final grade for this subject will be 0.
The proposed teaching methodology and assessment may be subject tochange depending on the attendance restrictions imposed by the health authorities.

Assessment Activities

Title Weighting Hours ECTS Learning Outcomes
Delivery of individual works 20% 15 0.6 7, 3, 1, 4, 8, 9, 12, 24, 22, 16, 17, 18, 19, 20, 5, 10
Group practice presentations 40% 15 0.6 7, 2, 3, 1, 4, 8, 6, 9, 12, 13, 14, 15, 24, 22, 16, 17, 18, 19, 20, 5, 10
Theoric exam 40% 3 0.12 7, 23, 21, 11, 13, 18, 10


Cha, Meeyoung; Haddadi, Hamed; Benevenuto, Fabrício; Gummadi, Krishna P. (2010). “Measuring user influence in Twitter: The million follower fallacy”. En: ICWSM, 2010. http://snap.stanford.edu/class/cs224w-readings/ cha10influence.pdf

Croll, Alistar & Power, Sean. Complete Web Monitoring. O'Reilly Media, 2009.

Kaushik, Avinash. Analítica Web 2.0: El arte de analizar resultados y la ciencia de centrarse en el cliente. Gestión 2000, 2011.

Lara-Navarra, Pablo; López-Borrull, Alexandre; Sánchez-Navarro, Jordi & Yànez, Pau. Medición de la influencia de usuarios en redes sociales: propuesta Socialengagement. El profesional de la información, 2018, julio-agosto, v. 27, n. 4. http://profesionaldelainformacion.com/contenidos/2018/jul/18.pdf

Muñoz Vera, Gemma & Elosegui, Tristán. El arte de medir: Manual de analítica Web. Bresca, 2011.



Data analysis and visualization tools