The objective of this subject is for the student to be capable of tackling real-world data analysis problems. The aim of the course is to analyze the applicability of analysis techniques in business problems and to learn which type of technique should be employed for each type of problem. Different analysis tools will be learned, as well as how to set the parameters based on the problem. In addition to the business domain, the domains of text analysis and time series analysis will be examined, learning the specific techniques for these domains as well as their parameterization. The final objective of the course is for the student to be able to develop a complete data analysis project in a real-world case.

1. Introduction 1.1.- Fundamental concepts 1.2.- Explainable AI 2.- Business intelligence 2.1.- Selection and transformation of attributes 2.2.- Segmentation, prediction and identification of patterns 2.3.- Advanced analysis techniques 2.4.- Tools 2.5.- Comparison of techniques and parameters 3.- Domain dependent analysis 3.1.- Text analysis 3.2.- Time series analysis 3.3.- Other domains 4. Case study 4.1.- Loading and data processing 4.2.- Application of data analysis methodology 4.3.- Conclusions

ACTIVITIES AF1 - Theoretical class. - [11.67 hours with 100% attendance, 0.39 ECTS] AF2 - Practical classes - [1.67 hours with 100% attendance, 0.06 ECTS] AF3 - Theoretical practical classes - [10 hours with 100% attendance, 0.33 ECTS] AF5 - Tutorials - [3 hours with 25% attendance, 0.10 ECTS] AF6 - Group work - [13 hours with 0% attendance, 0.43 ECTS] AF7 - Individual student work - [50.66 hours with 0% attendance, 1.69 ECTS] TEACHING METHODOLOGY MD1 - Lectures in the teacher's class with the support of computer and audiovisual media, in which the main concepts of the subject are developed and the bibliography is provided to complement the students' learning. MD2 - Critical reading of texts recommended by the professor of the subject: Press articles, reports, manuals and / or academic articles, either for later discussion in class, or to expand and consolidate the knowledge of the subject. MD3 - Resolution of practical cases, problems, etc ... raised by the teacher individually or in groups MD4 - Presentation and discussion in class, under the moderation of the teacher of topics related to the content of the subject, as well as practical cases MD5 - Preparation of works and reports individually or in groups