Bachelor’s Degree in Business Analytics

2.1. Knowledge or content

• K1. Know the organizational foundations of the different functional areas of the company, as well as the way in which they interrelate to respond to the demands of society and the market.
• K2. Describe the legal, micro and macroeconomic factors that condition the environment in which a company operates.
• K3. Recall the theoretical and practical foundations of mathematical, statistical and econometric models and techniques in real studies and problems in the business field.
• K4. Show the data visualization and data presentation techniques that facilitate data collection in the business environment.
• K5. Know how the most commonly used programming languages work in the context of data analysis for business.
• K6. Name the differences between the basic machine learning techniques and their applications for decision making in the business field.
• K7. Identify the financial risks that may compromise the viability of a company.

2.2. Skills or abilities

• H1. Utilize established accounting methods to record economic transactions that impact a company's assets and results, thereby understanding the economic-financial situation of a business project.
• H2. Apply financial derivatives to investment portfolios to manage and control company risks.
• H3. Employ statistical models or techniques to address real-world problems in various areas of the company.
• H4. Interpret the results of econometric and time series models for predictive purposes within the business field.
• H5. Create efficient reports and visualizations for data-driven decision-making within the company.
• H6. Develop programs in the most commonly used languages in business analysis, tailored to different problems of modeling, analysis, and data visualization.
• H7. Implement solutions related to data ingestion, extraction, and loading, applicable to the realm of business intelligence.
• H8. Apply supervised learning algorithms, reinforcement learning, and unsupervised learning to real company problems.
• H9. Address a problem by identifying the options and benefits of using language processing techniques within business analysis.
• H10. Utilize artificial intelligence techniques to solve predictive problems within business analysis.

2.3. Competences

• C1. Utilize quantitative tools and instruments in professional practice to obtain, diagnose, and analyze business information within an economic and social context.
• C2. Integrate the knowledge acquired throughout the degree and demonstrate an understanding of the theoretical and practical aspects relevant to real-world business problems.
• C3. Manage situations that require the development of new solutions through the processing of large amounts of data in the professional business environment.
• C4. Communicate knowledge, methodologies, and solutions for business problems clearly and precisely to all types of audiences, whether specialized or not.
• C5. Identify personal training needs for successful professional development and organize self-directed learning with a high degree of autonomy in various contexts.
• C6. Apply the knowledge acquired in the degree to real-world contexts by participating in work teams in the field of business analysis.
• C7. Utilize the knowledge acquired in the degree to develop, present, and defend a project in the area of business analysis, synthesizing the learning outcomes achieved during the degree.

Transversal competences related to the Sustainable Development Goals:

• TC1. Act with ethics and professional responsibility when facing social, environmental, and economic challenges, guided by democratic principles, values, and the Sustainable Development Goals.
• TC2. Evaluate the ethical consequences of decisions in specific situations, considering their impact on society and professional responsibility.
• TC3. Make informed judgments regarding sustainability and climate change.
• TC4. Demonstrate respect for diversity and adhere to the principles of universal accessibility and design for all people.
• TC5. Contribute to the design, development, and implementation of solutions that address social demands, with the Sustainable Development Goals as a reference.

Calendar and Schedules

Schedules

Admission

For the purposes of pre-admission and admission, the evaluation of the candidate will be made on a scale ranging from 0 to 10 points taking into account the following criteria and percentages:

• Academic record [60%]: The grades obtained by the candidate in their previous studies will be assessed.
• Structured personal interview [30%]: The suitability of the candidate will be assessed by virtue of their experience, knowledge, technical and professional skills required to successfully carry out their intended studies. Their motivation and attitudes will also be assessed, as well as other personal aspects that contribute to their adequate adjustment to the chosen studies. The interview may be conducted in the language in which the studies are taught.
• Presentation document of the candidate [10%]: In a document prepared personally, the candidate will explain their motivation and interest in the requested studies, as well as any other personal circumstance that they consider relevant for the selection process.

Additionally, candidates must pass a specific competence test, to determine the basic knowledge and minimum level that a candidate must have to be able to take the Bachelor's Degree, and it will be assessed by the Directors of the program during the structured personal interview with the candidate if they deem it necessary.

In the event that the candidate's mother tongue is not Spanish, they must prove a B2 level of Spanish, through any accredited certificate.