With the best developed distance learning systems, this MBA will allow you to learn in a contextual way, learning the practical skills that you need"

This intensive specialization program is aimed at those interested in attaining a higher level of knowledge of Corporate Technical Data Science Management. Its teaching program is unique for its careful selection of technologies, including the most recently incorporated and in demand in the business world. In addition, the incorporation of specific modules for the improvement of business vision and the management of multidisciplinary teams, makes this program different and capable of covering a large part of the educational needs of any professional who wishes to position themselves as a reference in the theoretical and practical knowledge of the latest technologies.

In today's rapidly changing world, the proliferation of new technologies is a constant. Currently, we are accustomed to cutting-edge tools, platforms or technologies that are becoming obsolete with reduced applicability in the business environment. 

Similarly, it is only natural that emerging or non-existent technologies in niche markets become trends in more general areas. 

Without any doubt, this is an unstoppable and constantly evolving process, the maximum exponent of the current technological revolution, which forces IT professionals to specialise on a permanent basis.  

In view of this situation, this MBA in Corporate Technical Data Science Management is offered as a comprehensive program that includes the most advanced and demanded technologies in the business environment. 

Therefore, in an exercise of synthesis, from both a technical and business perspective, a set of subjects that are not usually covered by general educational programs has been selected, with the aim of providing students with the necessary technological knowledge to address multiple current technological problems through the use of the most appropriate and advanced techniques. 

As such, the combination of both purely technical and business subjects, make this Professional Master's Degree a cutting-edge specialization especially oriented to professionals who seek to learn the most currently widespread technologies, or a higher level of knowledge of these. 

The main objective is to enable students to apply the knowledge acquired in this course to the real world, in a work environment that reproduces the conditions that may be encountered in the future, in a rigorous and realistic manner. 

As it is a 100% online program, students will not have to give up personal or professional obligations. Upon completion of the program, students will have updated their knowledge and will be in possession of an incredibly prestigious degree that will allow them to advance both personally and professionally.

An intensive professional growth program that will allow you to intervene in a sector with a growing demand for professionals” 

This Professional master’s degree in Corporate Technical Data Science Management contains the most complete and up-to-date program on the market. The most important features include:

• Practical cases presented by experts in Advanced IT Technologies
• The graphic, schematic and eminently practical contents with which it is conceived gather scientific and practical information on those disciplines that are indispensable for professional practice
• Practical exercises where the self-assessment process can be carried out to improve learning
• Its special emphasis on innovative methodologies
• Theoretical lessons, questions to the expert, debate forums on controversial topics, and individual reflection assignments
• Content that is accessible from any fixed or portable device with an Internet connection

A high-quality program that will allow students to advance quickly and steadily in knowledge acquisition, with the scientific rigor of a global quality teaching"

The program’s teaching staff includes professionals from the sector who contribute their work experience to this training program, as well as renowned specialists from leading societies and prestigious universities. 

The multimedia content, developed with the latest educational technology, will provide the professional with situated and contextual learning, i.e., a simulated environment that will provide immersive education programmed to learn in real situations. 

This program is designed around Problem-Based Learning, whereby the professional must try to solve the different professional practice situations that arise during the course. For this purpose, students will be assisted by an innovative interactive video system created by renowned and experienced experts. 

A complete and cutting-edge program that will allow you to progressively and completely acquire the knowledge you need to work in this sector"

Comprehensive yet focused; this program will provide you with the specific knowledge IT professionals need to compete among the best in the sector"

The syllabus has been designed based on educational efficiency, carefully selecting the contents to offer a comprehensive course, which includes all the fields of study that are essential to achieve real knowledge of the subject. Including the latest updates and aspects of the field. Therefore, the syllabus consists of modules that offer a broad perspective of.
Corporate Technical Data Science Management From first module, students will see their knowledge expanding, which will enable them to develop professionally, knowing that they can count on the support of a team of experts.

All the subjects and areas of knowledge have been compiled in a complete and absolutely up-to-date syllabus, in order to bring the student to the highest theoretical and practical level"

Module 1. The Main Information Management Systems

1.1. ERP and CRM

1.1.1. ERP
1.1.2. CRM
1.1.3. Differences between ERP and CRM Selling Point
1.1.4. Business Success

1.2. ERP

1.2.1. ERP
1.2.2. Types of ERPs
1.2.3. Development of an ERP Implementation Project
1.2.4. ERP Resource Optimizer
1.2.5. Architecture of an ERP System

1.3. Information Provided by the ERP

1.3.1. Information Provided by the ERP
1.3.2. Advantages and Disadvantages
1.3.3. The Information

1.4. ERP Systems

1.4.1. Current ERP Systems and Tools
1.4.2. Decision Making
1.4.3. Day-to-Day with ERP

1.5. CRM: The Implementation Project

1.5.1. The CRM The Implementation Project
1.5.2. The CRM as a Commercial Tool
1.5.3. Strategies for the Information System

1.6. CRM: Customer Loyalty

1.6.1. Starting Point
1.6.2. Sales or Loyalty
1.6.3. Factors for Success in our Loyalty System
1.6.4. Multi-Channel Strategies
1.6.5. Design of Loyalty Actions
1.6.6. E-Loyalty

1.7. CRM: Communication Campaigns

1.7.1. Communication Actions and Plans
1.7.2. Importance of the Informed Customer
1.7.3. Listening to the Client

1.8. CRM: Dissatisfaction Prevention

1.8.1. Customer Cancellations
1.8.2. Detecting Errors in Time
1.8.3. Improvement Processes
1.8.4. Recovery of the Dissatisfied Customer

1.9. CRM: Special Communication Actions

1.9.1. Objectives and Planning of a Company Event
1.9.2. Design and Realization of the Event
1.9.3. Actions from the Department
1.9.4. Result Analysis

1.10. Relational Marketing

1.10.1. Implantation. Errors
1.10.2. Methodology, Segmentation and Processes
1.10.3. Performance, According to the Department
1.10.4. CRM Tools

Module 2. Data Types and Life Cycle

2.1. Statistics

2.1.1. Statistics: Descriptive Statistics, Statistical Inferences
2.1.2. Population, Sample, Individual
2.1.3. Variables: Definition, Measurement Scales

2.2. Types of Data Statistics

2.2.1. According to Type

2.2.1.1. Quantitative: Continuous Data and Discrete Data
2.2.1.2. Qualitative: Binomial Data, Nominal Data and Ordinal Data

2.2.2. According to their Shape

2.2.2.1. Numeric
2.2.2.2. Text:
2.2.2.3. Logical

2.2.3. According to its Source

2.2.3.1. Primary
2.2.3.2. Secondary

2.3. Life Cycle of Data

2.3.1. Stages of the Cycle
2.3.2. Milestones of the Cycle
2.3.3. FAIR Principles

2.4. Initial Stages of the Cycle

2.4.1. Definition of Goals
2.4.2. Determination of Resource Requirements
2.4.3. Gantt Chart
2.4.4. Data Structure

2.5. Data Collection

2.5.1. Methodology of Data Collection
2.5.2. Data Collection Tools
2.5.3. Data Collection Channels

2.6. Data Cleaning

2.6.1. Phases of Data Cleansing
2.6.2. Data Quality
2.6.3. Data Manipulation (with R)

2.7. Data Analysis, Interpretation and Evaluation of Results

2.7.1. Statistical Measures
2.7.2. Relationship Indexes
2.7.3. Data Mining

2.8. Data Warehouse (Datawarehouse)

2.8.1. Elements that Comprise it
2.8.2. Design
2.8.3. Aspects to Consider

2.9. Data Availability

2.9.1. Access
2.9.2. Uses
2.9.3. Security

2.10. Data Protection Law

2.10.1. Good Practices
2.10.2. Other Regulatory Aspects

Module 3. Number Machine Learning

3.1. Knowledge in Databases

3.1.1. Data Pre-Processing
3.1.2. Analysis
3.1.3. Interpretation and Evaluation of the Results

3.2. Machine Learning

3.2.1. Supervised and Unsupervised Learning
3.2.2. Reinforcement Learning
3.2.3. Semi-Supervised Learning: Other Learning Models

3.3. Classification

3.3.1. Decision Trees and Rule-Based Learning
3.3.2. Support Vector Machines (SVM) and K-Nearest Neighbor (KNN) Algorithms.
3.3.3. Metrics for Sorting Algorithms

3.4. Regression

3.4.1. Linear and Logistic Regression
3.4.2. Non-Linear Regression Models
3.4.3. Time Series Analysis
3.4.4. Metrics for Regression Algorithms

3.5. Clustering

3.5.1. Hierarchical Grouping
3.5.2. Partitional Grouping
3.5.3. Metrics for Clustering Algorithms

3.6. Association Rules

3.6.1. Measures of Interest
3.6.2. Rule Extraction Methods
3.6.3. Metrics for Association Rule Algorithms

3.7. Multiclassifiers

3.7.1. “Bootstrap Aggregation" or "Bagging"
3.7.2. “Random “Forests” Algorithm
3.7.3. “Boosting” Algorithm

3.8. Probabilistic Reasoning Models

3.8.1. Probabilistic reasoning
3.8.2. Bayesian Networks or Belief Networks
3.8.3. “Hidden Markov Models”

3.9. Multilayer Perceptron

3.9.1. Neural Network:
3.9.2. Machine Learning with Neural Networks
3.9.3. Gradient Descent, Backpropagation and Activation Functions
3.9.4. Implementation of an Artificial Neural Network

3.10 Deep Learning

3.10.1. Deep Neural Networks. Introduction
3.10.2. Convolutional Networks
3.10.3. Sequence Modelling
3.10.4. Tensorflow and Pytorch

Module 4. Web Analytics

4.1. Web Analytics

4.1.1. Introduction
4.1.2. Evolution of Web Analytics
4.1.3. Analysis Process

4.2. Google Analytics

4.2.1. Google Analytics
4.2.2. Use
4.2.3. Objectives

4.3. Hits. Interactions with the Website

4.3.1. Basic Metrics
4.3.2. KPI (Key Performance Indicators)
4.3.3. Adequate Conversion Rates

4.4. Frequent Dimensions

4.4.1. Source
4.4.2. Medium
4.4.3. Keyword
4.4.4. Campaign
4.4.5. Personalized Labelling

4.5. Setting up Google Analytics

4.5.1. Installation. Creating the Account
4.5.2. Versions of the Tool: UA/GA4
4.5.3. Tracking Label
4.5.4. Conversion Objectives

4.6. Organization of Google Analytics

4.6.1. Account
4.6.2. Property
4.6.3. View

4.7. Google Analytics Reports

4.7.1. In Real Time
4.7.2. Audience
4.7.3. Acquisition
4.7.4. Behavior
4.7.5. Conversions
4.7.6. E-Commerce

4.8. Google Analytics Advanced Reports

4.8.1. Personalized Reports
4.8.2. Panels
4.8.3. APIs

4.9. Filters and Segments

4.9.1. Filter
4.9.2. Segment
4.9.3. Types of Segments: Predefined/Customized
4.9.4. Remarketing Lists

4.10. Digital Analytics Plan

4.10.1. Measurement
4.10.2. Implementation in the Technological Environment
4.10.3. Conclusions

Module 5. Scalable and Reliable Mass Data Usage Systems

5.1. Scalability, Reliability and Maintainability

5.1.1. Scales
5.1.2. Reliability
5.1.3. Maintainability

5.2. Data Models

5.2.1. Evolution of Data Models
5.2.2. Comparison of Relational Model with Document-Based NoSQL Model
5.2.3. Network Model

5.3. Data Storage and Retrieval Engines

5.3.1. Structured Log Storage
5.3.2. Storage in Segment Tables
5.3.3. Trees B

5.4. Services, Message Passing and Data Encoding Formats

5.4.1. Data Flow in REST Services
5.4.2. Data Flow in Message Passing
5.4.3. Message Sending Formats

5.5. Replication

5.5.1. CAP Theorem
5.5.2. Consistency Models
5.5.3. Models of Replication Based on Leader and Follower Concepts

5.6. Distributed Transactions

5.6.1. Atomic Operations
5.6.2. Distributed Transactions from Different Approaches Calvin, Spanner
5.6.3. Serializability

5.7. Partitions

5.7.1. Types of Partitions
5.7.2. Indexes in Partitions
5.7.3. Partition Rebalancing

5.8. Batch Processing

5.8.1. Batch Processing
5.8.2. MapReduce
5.8.3. Post-MapReduce Approaches

5.9. Data Stream Processing

5.9.1. Messaging Systems
5.9.2. Persistence of Data Flows
5.9.3. Uses and Operations with Data Flows

5.10. Case Uses. Twitter, Facebook, Uber

5.10.1. Twitter: The Use of Caches
5.10.2. Facebook: Non-Relational Models
5.10.3. Uber: Different Models for Different Purposes

Module 6. System Administration for Distributed Deployments

6.1. Classic Administration. The Monolithic Model

6.1.1. Classical Applications. The Monolithic Model
6.1.2. System Requirements for Monolithic Applications
6.1.3. The Administration of Monolithic Systems
6.1.4. Automation

6.2. Distributed Applications. The Microservice

6.2.1. Distributed Computing Paradigm
6.2.2. Microservices-Based Models
6.2.3. System Requirements for Distributed Models
6.2.4. Monolithic Applications vs. Distributed Applications

6.3. Tools for Resource Exploitation

6.3.1. “Iron” Management
6.3.2. Virtualization
6.3.3. Emulation
6.3.4. Paravirtualization

6.4. IaaS, PaaS and SaaS Models

6.4.1. LaaS Model
6.4.2. PaaS Model
6.4.3. SaaS Model
6.4.4. Design Patterns

6.5. Containerization

6.5.1. Virtualization with Cogroups
6.5.2. Containers
6.5.3. From Application to Container
6.5.4. Container Orchestration

6.6. Clustering

6.6.1. High Performance and High Availability
6.6.2. High Availability Models
6.6.3. Cluster as SaaS Platform
6.6.4. Cluster Securitization

6.7. Cloud Computing

6.7.1. Clusters vs Clouds
6.7.2. Types of Clouds
6.7.3. Cloud Service Models
6.7.4. Oversubscription

6.8. Monitoring and Testing

6.8.1. Types of Monitoring
6.8.2. Visualization
6.8.3. Infrastructure Tests
6.8.4. Chaos Engineering

6.9. Study Case: Kubernetes

6.9.1. Structure
6.9.2. Administration.
6.9.3. Deployment of Services
6.9.4. Development of Services for K8S

6.10. Study Case: OpenStack

6.10.1. Structure
6.10.2. Administration
6.10.3. Deployment
6.10.4. Development of Services for OpenStack

Module 7. Internet of Things

7.1. Internet of Things (IoT)

7.1.1. The Internet of the Future
7.1.2. Internet of Things and Industrial Internet of Things
7.1.3. The Industrial Internet Consortium

7.2. Architecture of Reference

7.2.1. The Architecture of Reference
7.2.2. Layers and Components

7.3. IoT Devices

7.3.1. Classification
7.3.2. Components
7.3.3. Sensors and Actuators

7.4. Communication Protocols

7.4.1. Classification
7.4.2. OSI Model
7.4.3. Technologies

7.5. IoT and IIoT platforms

7.5.1. The IoT Platform
7.5.2. General Purpose Cloud Platforms
7.5.3. Industrial Platforms
7.5.4. Open Code Platforms

7.6. Data Management on IoT Platforms

7.6.1. Management Mechanisms
7.6.2. Open Data
7.6.3. Exchange of Data
7.6.4. Data Visualization

7.7. IoT Security

7.7.1. Security Requirements
7.7.2. Security Areas
7.7.3. Security Strategies
7.7.4. IIoT Security

7.8. IoT Systems Application Areas

7.8.1. Intelligent Cities
7.8.2. Health and Fitness
7.8.3. Smart Home
7.8.4. Other Applications

7.9. Application of IIoT to Different Industrial Sectors

7.9.1. Fabrication
7.9.2. Transport
7.9.3. Energy
7.9.4. Agriculture and Livestock
7.9.5. Other Sectors

7.10. Integration of IIoT in the Industry 4.0 Model

7.10.1. IoRT (Internet of Robotics Things)
7.10.2. 3D Additive Manufacturing
7.10.3. Big Data Analytics

Module 8. Project Management and Agile Methodologies

8.1. Project Management

8.1.1. The Project
8.1.2. Phases of a Project
8.1.3. Project Management

8.2. PMI Methodology for Project Management

8.2.1. PMI (Project Management Institute)
8.2.2. PMBOK
8.2.3. Difference between Project, Program and Project Portfolio
8.2.4. Evolution of Organizations Working with Projects
8.2.5. Process Assets in Organizations

8.3. PMI Methodology for Project Management: Process

8.3.1. Groups of Processes
8.3.2. Knowledge Areas
8.3.3. Process Matrix

8.4. Agile Methodologies for Project Management

8.4.1. VUCA Context (Volatility, Uncertainty, Complexity and Ambiguity)
8.4.2. Agile Values
8.4.3. Principles of the Agile Manifesto

8.5. Agile SCRUM Framework for Project Management

8.5.1. Scrum
8.5.2. The Pillars of the Scrum Methodology
8.5.3. The Values in Scrum

8.6. Agile SCRUM Framework for Project Management Process

8.6.1. The Scrum Process
8.6.2. Typified Roles in a Scrum Process
8.6.3. The Ceremonies of Scrum

8.7. Agile SCRUM Framework for Project Management Artifacts

8.7.1. Artefacts in the Scrum Process
8.7.2. The Scrum Team
8.7.3. Metrics for Evaluating the Performance of a Scrum Team

8.8. Agile KANBAN Framework for Project Management. Kanban Method

8.8.1. Kanban
8.8.2. Benefits of Kanban
8.8.3. Kanban Method Components

8.9. Agile KANBAN Framework for Project Management. Kanban Method Practices

8.9.1. The Values of Kanban
8.9.2. Principles of the Kanban Method
8.9.3. General Practices of the Kanban Method
8.9.4. Metrics for Kanban Performance Evaluation

8.10. Comparison: PMI, SCRUM y KANBAN

8.10.1. PMI – SCRUM
8.10.2. PMI – KANBAN
8.10.3. SCRUM – KANBAN

Module 9. Communication, Leadership and Team Management

9.1. Organizational Development in Business

9.1.1. Climate, Culture and Organizational Development in the Company
9.1.2. Human Capital Management

9.2. Direction Models Decision Making

9.2.1. Paradigm Shift in Management Models
9.2.2. Management Process of the Technology Company
9.2.3. Decision-Making. Planning Instruments

9.3. Leadership Delegation and Empowerment

9.3.1. Leadership
9.3.2. Delegation and Empowerment
9.3.3. Performance Evaluation

9.4. Leadership Knowledge and Talent Management

9.4.1. Talent Management in the Company
9.4.2. Engagement Management in the Company
9.4.3. Improving Communication in the Company

9.5. Coaching Applied to Business

9.5.1. Executive Coaching
9.5.2. Team Coaching

9.6. Mentoring Applied to Business

9.6.1. Mentor Profile
9.6.2. The 4 Processes of a Mentoring Program
9.6.3. Tools and Techniques in a Mentoring Process
9.6.4. Benefits of Mentoring in the Business Environment

9.7. Team Management I. Interpersonal Relations

9.7.1. Interpersonal Relationships

9.7.1.1. Relational Styles: Focuses
9.7.1.2. Effective Meetings and Agreements in Difficult Situations

9.8. Team Management II. The Conflicts

9.8.1. The Conflicts
9.8.2. Preventing, Addressing and Resolving Conflict

9.8.2.1. Strategies to Prevent Conflict
9.8.2.2. Conflict Management. Basic Principles
9.8.2.3. Conflict Resolution Strategies

9.8.3. Stress and Work Motivation

9.9. Team Management III. Negotiation

9.9.1. Negotiation at the Managerial Level in Technology Companies
9.9.2. Styles of Negotiation
9.9.3. Negotiation Phases

9.9.3.1. Barriers to Overcome in Negotiations

9.10. Team Management IV. Negotiation Techniques

9.10.1. Negotiation Techniques and Strategies

9.10.1.1. Strategies and Main Types of Negotiation
9.10.1.2. Negotiation Tactics and Practical Issues

9.10.2. The Figure of the Negotiating Subject

Module 10. Leadership, Ethics and Social Responsibility in Companies 

10.1. Globalization and Governance 

10.1.1. Governance and Corporate Governance 
10.1.2. The Fundamentals of Corporate Governance in Companies 
10.1.3. The Role of the Board of Directors in  the Corporate Governance Framework 

10.2. Leadership 

10.2.1. Leadership A Conceptual Approach 
10.2.2. Leadership in Companies 
10.2.3. The Importance of Leaders in Business Management 

10.3. Cross Cultural Management 

10.3.1. Cross Cultural Management Concept
10.3.2. Contributions to Knowledge of National Cultures 
10.3.3. Diversity Management 

10.4. Management and Leadership Development 

10.4.1. Concept of Management Development 
10.4.2. Concept of Leadership 
10.4.3. Leadership Theories 
10.4.4. Leadership Styles 
10.4.5. Intelligence in Leadership 
10.4.6. The Challenges of Today's Leader 

10.5. Business Ethics 

10.5.1. Ethics and Morality 
10.5.2. Business Ethics 
10.5.3. Leadership and Ethics in Companies 

10.6. Sustainability 

10.6.1. Sustainability and Sustainable Development 
10.6.2. The 2030 Agenda 
10.6.3. Sustainable Companies 

10.7. Corporate Social Responsibility 

10.7.1. International Dimensions of Corporate Social Responsibility 
10.7.2. Implementing Corporate Social Responsibility 
10.7.3. The Impact and Measurement of Corporate Social Responsibility 

10.8. Responsible Management Systems and Tools 

10.8.1. CSR: Corporate Social Responsibility 
10.8.2. Essential Aspects for Implementing a Responsible Management Strategy 
10.8.3. Steps for the Implementation of a Corporate Social Responsibility Management System 
10.8.4. CSR Tools and Standards 

10.9. Multinationals and Human Rights 

10.9.1. Globalization, Multinational Companies and Human Rights 
10.9.2. Multinational Corporations and International Law
10.9.3. Legal Instruments for Multinationals in the Area of Human Rights

10.10. Legal Environment and Corporate Governance 

10.10.1. International Rules on Importation and Exportation 
10.10.2. Intellectual and Industrial Property 
10.10.3. International Labor Law  

Module 11. People and Talent Management 

11.1. Strategic People Management 

11.1.1. Strategic Human Resources Management 
11.1.2. Strategic People Management 

11.2. Human Resources Management by Competencies 

11.2.1. Analysis of the Potential 
11.2.2. Remuneration Policy 
11.2.3. Career/Succession Planning 

11.3. Performance Evaluation and Performance Management 

11.3.1. Performance Management 
11.3.2. Performance Management: Objectives and Process 

11.4. Innovation in Talent and People Management 

11.4.1. Strategic Talent Management Models 
11.4.2. Talent Identification, Training and Development 
11.4.3. Loyalty and Retention 
11.4.4. Proactivity and Innovation 

11.5. Motivation 

11.5.1. The Nature of Motivation 
11.5.2. Expectations Theory 
11.5.3. Needs Theory 
11.5.4. Motivation and Financial Compensation 

11.6. Developing High Performance Teams 

11.6.1. High-Performance Teams: Self-Managed Teams 
11.6.2. Methodologies for the Management of High Performance Self-Managed Teams 

11.7. Change Management 

11.7.1. Change Management 
11.7.2. Type of Change Management Processes 
11.7.3. Stages or Phases in the Change Management Process 

11.8. Negotiation and Conflict Management 

11.8.1. Negotiation 
11.8.2. Conflict Management  
11.8.3. Crisis Management 

11.9. Executive Communication 

11.9.1. Internal and External Communication in the Corporate Environment 
11.9.2. Communication Departments 
11.9.3. The Person in Charge of Communication of the Company The Profile of the Dircom 

11.10. Productivity, Attraction, Retention and Activation of Talent 

11.10.1. Productivity 
11.10.2. Talent Attraction and Retention Levers 

Module 12. Economic and Financial Management 

12.1. Economic Environment 

12.1.1. Macroeconomic Environment and the National Financial System 
12.1.2. Financial Institutions 
12.1.3. Financial Markets 
12.1.4. Financial Assets 
12.1.5. Other Financial Sector Entities 

12.2. Executive Accounting 

12.2.1. Basic Concepts 
12.2.2. The Company's Assets 
12.2.3. The Company's Liabilities 
12.2.4. The Company's Net Worth 
12.2.5. The Income Statement 

12.3. Information Systems and Business Intelligence 

12.3.1. Fundamentals and Classification 
12.3.2. Cost Allocation Phases and Methods 
12.3.3. Choice of Cost Center and Impact 

12.4. Budget and Management Control 

12.4.1. The Budget Model 
12.4.2. The Capital Budget 
12.4.3. The Operating Budget 
12.4.5. Treasury Budget 
12.4.6. Budget Monitoring 

12.5. Financial Management 

12.5.1. The Company's Financial Decisions 
12.5.2. Financial Department 
12.5.3. Cash Surpluses 
12.5.4. Risks Associated with Financial Management 
12.5.5. Financial Administration Risk Management 

12.6. Financial Planning 

12.6.1. Definition of Financial Planning 
12.6.2. Actions to be Taken in Financial Planning 
12.6.3. Creation and Establishment of the Business Strategy 
12.6.4. The Cash Flow Table 
12.6.5. The Working Capital Table 

12.7. Corporate Financial Strategy 

12.7.1. Corporate Strategy and Sources of Financing 
12.7.2. Financial Products for Corporate Financing 

12.8. Strategic Financing 

12.8.1. Self-Financing 
12.8.2. Increase in Equity 
12.8.3. Hybrid Resources 
12.8.4. Financing Through Intermediaries 

12.9. Financial Analysis and Planning 

12.9.1. Analysis of the Balance Sheet 
12.9.2. Analysis of the Income Statement 
12.9.3. Profitability Analysis 

12.10. Analyzing and Solving Cases/Problems 

12.10.1. Financial Information on Industria de Diseño y Textil, S.A. (INDITEX) 

Module 13. Commercial and  Strategic Marketing Management 

13.1. Commercial Management 

13.1.1. Conceptual Framework of Commercial Management 
13.1.2. Business Strategy and Planning 
13.1.3. The Role of Sales Managers 

13.2. Marketing 

13.2.1. The Concept of Marketing 
13.2.2. Basic Elements of Marketing 
13.2.3. Marketing Activities of the Company 

13.3. Strategic Marketing Management 

13.3.1. The Concept of Strategic Marketing 
13.3.2. Concept of Strategic Marketing Planning 
13.3.3. Stages in the Process of Strategic Marketing Planning 

13.4. Digital Marketing and e-Commerce 

13.4.1. Digital Marketing and E-commerce Objectives 
13.4.2. Digital Marketing and Media Used  
13.4.3. E-Commerce General Context 
13.4.4. Categories of E-commerce 
13.4.5. Advantages and Disadvantages of E-commerce Versus Traditional Commerce 

13.5. Digital Marketing to Reinforce a Brand 

13.5.1. Online Strategies to Improve Your Brand's Reputation 
13.5.2. Branded Content and Storytelling 

13.6. Digital Marketing to Attract and Retain Customers 

13.6.1. Loyalty and Engagement Strategies through the Internet 
13.6.2. Visitor Relationship Management 
13.6.3. Hypersegmentation 

13.7. Managing Digital Campaigns 

13.7.1. What is a Digital Advertising Campaign? 
13.7.2. Steps to Launch an Online Marketing Campaign 
13.7.3. Mistakes in Digital Advertising Campaigns 

13.8. Sales Strategy  

13.8.1. Sales Strategy 
13.8.2. Sales Methods 

13.9. Corporate Communication 

13.9.1. Concept 
13.9.2. The Importance of Communication in the Organization 
13.9.3. Type of Communication in the Organization 
13.9.4. Functions of Communication in the Organization 
13.9.5. Elements of Communication 
13.9.6. Communication Problems 
13.9.7. Communication Scenarios 

13.10. Digital Communication and Reputation 

13.10.1. Online Reputation 
13.10.2. How to Measure Digital Reputation? 
13.10.3. Online Reputation Tools  
13.10.4. Online Reputation Report 
13.10.5. Online Branding 

Module 14. Executive Management 

14.1. General Management 

14.1.1. The Concept of General Management  
14.1.2. The Role of the CEO 
14.1.3. The CEO and their Responsibilities 
14.1.4. Transforming the Work of Management 

14.2. Manager Functions: Organizational Culture and Approaches 

14.2.1. Manager Functions: Organizational Culture and Approaches 

14.3. Operations Management 

14.3.1. The Importance of Management 
14.3.2. Value Chain 
14.3.3. Quality Management 

14.4. Public Speaking and Spokesperson Education 

14.4.1. Interpersonal Communication 
14.4.2. Communication Skills and Influence 
14.4.3. Communication Barriers 

14.5. Personal and Organizational  Communications Tools 

14.5.1. Interpersonal Communication 
14.5.2. Interpersonal Communication Tools 
14.5.3. Communication in the Organization 
14.5.4. Tools in the Organization 

14.6. Communication in Crisis Situations 

14.6.1. Crisis 
14.6.2. Phases of the Crisis 
14.6.3. Messages: Contents and Moments 

14.7. Preparation of a Crisis Plan 

14.7.1. Analysis of Possible Problems 
14.7.2. Planning 
14.7.3. Adequacy of Personnel 

14.8. Emotional Intelligence  

14.8.1. Emotional Intelligence and Communication 
14.8.2. Assertiveness, Empathy, and Active Listening 
14.8.3. Self-Esteem and Emotional Communication 

14.9. Personal Branding 

14.9.1. Strategies for Personal Brand Development 
14.9.2. Personal Branding Laws 
14.9.3. Tools for Creating Personal Brands 

14.10. Leadership and Team Management 

14.10.1. Leadership and Leadership Styles 
14.10.2. Leader Capabilities and Challenges 
14.10.3. Managing Change Processes 
14.10.4. Managing Multicultural Teams

A unique specialization program that stands out due to the quality of its contents and its excellent teaching staff”