Reach the top of your career and achieve success thanks to TECH! You will have access to 10 unique Masterclasses, designed by an internationally renowned Business Intelligence specialist"

Why Study at TECH?

TECH is the world's largest 100% online business school. It is an elite business school, with a model based on the highest academic standards. A world-class center for intensive managerial skills training.   

TECH is a university at the forefront of technology, and puts all its resources at the student's disposal to help them achieve entrepreneurial success"

At TECH Global University

Innovation

The university offers an online learning model that combines the latest educational technology with the most rigorous teaching methods. A unique method with the highest international recognition that will provide students with the keys to develop in a rapidly-evolving world, where innovation must be every entrepreneur’s focus.

"Microsoft Europe Success Story", for integrating the innovative, interactive multi-video system.  

The Highest Standards

Admissions criteria at TECH are not economic. Students don't need to make a large investment to study at this university. However, in order to obtain a qualification from TECH, the student's intelligence and ability will be tested to their limits. The institution's academic standards are exceptionally high...  

95% of TECH students successfully complete their studies.

Networking

Professionals from countries all over the world attend TECH, allowing students to establish a large network of contacts that may prove useful to them in the future.  

100,000+ executives trained each year, 200+ different nationalities.

Empowerment

Students will grow hand in hand with the best companies and highly regarded and influential professionals. TECH has developed strategic partnerships and a valuable network of contacts with major economic players in 7 continents.  

500+ collaborative agreements with leading companies.

Talent

This program is a unique initiative to allow students to showcase their talent in the business world. An opportunity that will allow them to voice their concerns and share their business vision. 

After completing this program, TECH helps students show the world their talent. 

Multicultural Context

While studying at TECH, students will enjoy a unique experience in a program with a global vision. They will study in a multicultural context. through which they can learn about the operating methods in different parts of the world, and gather the latest information that best adapts to their business idea. 

TECH's students represent more than 200 different nationalities.   

Learn with the best

In the classroom, TECH teaching staff discuss how they have achieved success in their companies, working in a real, lively, and dynamic context. Teachers who are fully committed to offering a quality specialization that will allow students to advance in their career and stand out in the business world. 

TECH's teachers represent more than 20 different nationalities. 

TECH strives for excellence and, to this end, boasts a series of characteristics that make this university unique:   

Analysis

TECH explores the student’s critical side, their ability to question things, their problem-solving skills, as well as their interpersonal skills.  

Academic Excellence

TECH offers students the best online learning methodology. The university combines the Relearning methodology (the most internationally recognized postgraduate learning methodology) with Harvard Business School case studies. A complex balance of traditional and state-of-the-art methods, within the most demanding academic framework.   

TECH is the world’s largest online university. It currently boasts a portfolio of more than 10,000 university postgraduate programs and in today's new economy, volume + technology = a ground-breaking price. This way, TECH ensures that studying is not as expensive for students as it would be at another university.  

At TECH you will have access to Harvard Business School case studies"  

The MBA in Business Intelligence Management is an exceptional program that challenges the professional by directing their attention to success in the business world and the quality of services and human capital. It is a program that has been structured in such a way that the student not only acquires all the knowledge and skills sought, but also presents a unique and stimulating experience that will take them to the top of their professional capacity. 

You will learn how to base the management of emotions as a basic tool to influence the results of the company and your professional future" 

Syllabus

The MBA in Business Intelligence Management at TECH Global University is an intensive program that prepares students to face challenges and business decisions in the field of technology and within data and information generation systems. 

The content of the MBA in Business Intelligence Management is designed to promote control and strategic decision making in a successful business environment. 

Over the course of 2,700 hours, the student analyzes a plethora of practical cases through individual and team work. It is, therefore, an authentic immersion in real business situations. 

Therefore, this Professional master’s degree deals in depth with the concept of Business Intelligence from a disruptive, complete and up-to-date perspective, focused on solving the real needs of the business world. It is designed to train professionals who understand Business Intelligence with a strategic, international and innovative approach. 

A plan fully designed for the student, focused on their professional improvement, preparing them to achieve excellence in the field of Business intelligence. A program that understands both the needs of the student and the company, through innovative content based on the latest trends, supported by the best educational methodology and an exceptional faculty. 

This MBA takes place over 12 months and is divided into 15 modules:

Module 1. Enterprise Business Intelligence 
Module 2. Business Perspective 
Module 3. Data-Driven Business Transformation
Module 4. Data Visualization  
Module 5. Programming for Data Analysis
Module 6. Digital Marketing Analytics 
Module 7. Data Management
Module 8. Data Protection
Module 9. Business Intelligence and Artificial Intelligence: Strategies and Applications 
Module 10. Optimization of the Company's Human Capital 
Module 11. Leadership, Ethics and Social Responsibility in Companies
Module 12. People and Talent Management 
Module 13. Economic and Financial Management
Module 14. Commercial Management and Strategic Marketing 
Module 15. Executive Management

Where, When and How is it Taught?

TECH offers the possibility of taking this program completely online. Over the course of the 12 months, the student will be able to access all the contents of this program at any time, allowing them to self-manage their study time. 

Module 1. Business Intelligence in the Company 

1.1. Corporate Business Intelligence 

1.1.1. The World of Data
1.1.2. Relevant Concepts.
1.1.3. Main Characteristics
1.1.4. Solutions in Today's Market
1.1.5. Overall Architecture of a BI Solution
1.1.6. Cybersecurity in BI and Data Science

1.2. New Business Concept 

1.2.1. Why BI
1.2.2. Obtaining Information
1.2.3. BI in the Different Departments of the Company
1.2.4. Reasons to Invest in BI

1.3. Data Warehouse 

1.3.1. Definition and Objectives Data Warehouse and Data Mart
1.3.2. Architecture
1.3.3. Dimensional Modeling and its Types of Diagrams
1.3.4. Extraction, Transformation and Loading Process (ETL)
1.3.5. Metadata

1.4. Big Data and Data Capture

1.4.1. Capture
1.4.2. Transformation
1.4.3. Storage

1.5. Reporting Business Intelligence (BI) 

1.5.1. Database Structures
1.5.2. OLTP and OLAP Databases
1.5.3. Examples

1.6. Dashboards or Balanced Scorecards 

1.6.1. Control Panels
1.6.2. Decision Support Systems
1.6.3. Executive Information Systems 

1.7. Deep Learning

1.7.1. Deep Learning
1.7.2. Deep Learning Applications

1.8. Machine Learning

1.8.1. Machine Learning
1.8.2. Machine Learning Utilities 
1.8.3. Deep Learning vs. Machine Learning 

1.9. BI Tools and Solutions

1.9.1. Choosing the Best Tool
1.9.2. Microsoft Power BI, MicroStrategy y Tableau
1.9.3. SAP BI, SAS BI and Qlikview
1.9.4. Prometheus

1.10. BI Project Planning and Management 

1.10.1. First Steps to Define a BI Project
1.10.2. BI Solution for the Company
1.10.3. Requirements and Objectives

Module 2. Business Perspective 

2.1. The Company

2.1.1. Venture Capital Theory
2.1.2. Organizational Morphology: Size, Shape, Activity and Sectors
2.1.3. Organization and Resources
2.1.4. Management and Their Needs

2.2. The Company: Market and Customer

2.2.1. Market and Customer
2.2.2. Market Analysis and Segmentation

2.2.2.1. Direct and Indirect Competition
2.2.2.2. Competitive Advantage

2.3. SWOT Analysis

2.3.1. Business Strategy
2.3.2. DAFO Analysis
2.3.3. Objectives and Deadlines (SMART, C/M/L/P, Cascading).
2.3.4. Measuring Results: Knowing the Reality
2.3.5. Key Performance Indicators (KPI)

2.4. Information as an Asset

2.4.1. Information and Management
2.4.2. Life Cycle Information
2.4.3. Operational System and Strategic System

2.5. Integral Control Panel

2.5.1. Control Panels: Operational, Tactical and Strategic
2.5.2. CMI Definition
2.5.3. Financial Perspective
2.5.4. Customer Perspective
2.5.5. Internal Processes Perspective
2.5.6. Learning and Growth Perspective

2.6. Productivity Analysis

2.6.1. Income, Expenditures, Investment and Consumption
2.6.2. Cost Analysis and Allocation
2.6.3. ROI and Others Ratios of Interest

2.7. Distribution and Sales

2.7.1. Relevance of the Department
2.7.2. Channels and Equipment
2.7.3. Types of Sales and Consumption

2.8. Other Common Areas

2.8.1. Production and Service Delivery
2.8.2. Distribution and Logistics
2.8.3. Commercial Communication
2.8.4. Inbound Marketing

2.9. Data Management

2.9.1. Roles and Responsibilities (Managerial Roles and Technical Roles)
2.9.2.Stakeholder Identification
2.9.3. Information Management Systems (Intro and Types, without Technology Details)
2.9.4. Type of Operating Systems
2.9.5. Strategic or Decision Support Systems
2.9.6. Platforms for Information: Cloud Computing vs On Premise

2.10. Exploring the Information:

2.10.1. Intro SQL: Relational Databases Basic Concepts (DDL and DML, PK, FK, JOINS)
2.10.2. Networks and Communications: Public/Private Networks, Network/Subnet/Router Address and DNS. VPN Tunnel and SSH
2.10.3. Operating System: Standardized Data Models.
2.10.4. Strategic System: Multidimensional Modeling, OLAP and Graphic Dashboards
2.10.5. Strategic Analysis of BB.DD. and Report Composition

Module 3. Data-Driven Business Transformation

3.1. Big Data

3.1.1. Big Data in Companies
3.1.2. Concept of Value
3.1.3. Value Project Management

3.2. Customer Journey

3.2.1. Customer Life Cycle
3.2.2. Association of Campaigns to the Life Cycle
3.2.3. Campaign Metrics

3.3. Data Management for Campaigns

3.3.1. Datawarehouse and Datalab
3.3.2. Campaign Creation Tools
3.3.3. Drive Methods

3.4. Digital Marketing GDPR

3.4.1. Data Anonymization and Manipulation of Personal Data
3.4.2. Robinson Concept
3.4.3. Exclusion Lists

3.5. Control Panels

3.5.1. KPIs
3.5.2. Audience
3.5.3. Tools
3.5.4. Storytelling

3.6. Customer Analysis and Characterization

3.6.1. 360º Customer Vision
3.6.2. Relation of Analysis to Tactical Actions
3.6.3. Analysis Tools

3.7. Business Examples Applying Big Data Techniques

3.7.1. Upselling/Cross-Selling
3.7.2. Propensity Models
3.7.3. Risk Models
3.7.4. Predictions
3.7.5. Image Processing

Module 4. Data Visualization 

4.1. Data Visualization 

4.1.1. Data visualization
4.1.2. Importance of Data Analysis and Visualization
4.1.3. Evolution

4.2. The Design 

4.2.1. Use of Color
4.2.2. Composition and Typography
4.2.3. Recommendations

4.3. Types of Data

4.3.1. Qualitative
4.3.2. Quantitative
4.3.3. Temporary Data

4.4. Data Sets 

4.4.1. Files
4.4.2. Databases
4.4.3. Open Data
4.4.4. Streaming Data

4.5. Common Types of Representation 

4.5.1. Columns
4.5.2. Bars
4.5.3. Lines
4.5.4. Areas
4.5.5. Dispersion

4.6. Advanced Types of Representation 

4.6.1. Circulars
4.6.2. Rings
4.6.3. Bubbles
4.6.4. Maps

4.7. Application by Area 

4.7.1. Political Science and Sociology
4.7.2. Science
4.7.3. Marketing
4.7.4. Health and Well-being
4.7.5. Meteorology
4.7.6. Business and Finance

4.8. Storytelling 

4.8.1. Importance of Storytelling
4.8.2. History of Storytelling
4.8.3. Application of Storytelling

4.9. Visualization Software 

4.9.1. Commercials
4.9.2. Free
4.9.3. Online
4.9.4. Free Software

4.10. The Future of Data Visualization 

4.10.1. Virtual Reality
4.10.2. Augmented Reality
4.10.3. Artificial Intelligence

Module 5. Programming for Data Analysis 

5.1. Programming for Data Analysis

5.1.1. Language for Data Analysis 
5.1.2. Evolution and Characteristics of the Main Tools 
5.1.3. Installation and Configuration 

5.2. Types of Data

5.2.1. Basic Types 
5.2.2. Complex Types 
5.2.3. Other Structures

5.3. Structures and Operations 

5.3.1. Data Operations
5.3.2. Control Structures 
5.3.3. File Operations 

5.4. Data Extraction and Analysis 

5.4.1. Statistical Summaries 
5.4.2. Univariate Analysis 
5.4.3. Multivariate Analysis 

5.5. Visualization

5.5.1. Univariate Graphs 
5.5.2. Multivariable Graphs
5.5.3. Other Charts of Interest

5.6. Pre-processing 

5.6.1. The Importance of Data Quality 
5.6.2. Outlier Detection and Analysis 
5.6.3. Other Dataset Quality Factors 

5.7. Advanced Pre-processing

5.7.1. Subsampling 
5.7.2. Resampling 
5.7.3. Dimensionality Reduction

5.8. Data Modeling  

5.8.1. Modeling Phases 
5.8.2. Division of the Data Set 
5.8.3. Metrics for Prediction 

5.9. Advanced Data Modeling 

5.9.1. Unsupervised Models
5.9.2. Supervised Models 
5.9.3. Libraries for Modeling 

5.10. Tools and Good Practices

5.10.1. Best Practices for Modeling 
5.10.2. The Tools of a Data Analyst 
5.10.3. Conclusion and Bookstores of Interest

Module 6. Digital Marketing Analytics 

6.1. Web Analytics

6.1.1. Web Analytics Use
6.1.2. History
6.1.3. Applicable Methodology

6.2. Google Analytics

6.2.1. About Google Analytics
6.2.2. Metrics vs. Dimensions
6.2.3. Measurement Objectives

6.3. Conversion Metrics

6.3.1. Basic Metrics
6.3.2. Advanced Metrics or KPIs (Key Performance Indicators)
6.3.3. Conversions

6.4. Dimensions

6.4.1. Campaign/Keyword
6.4.2. Source/Media
6.4.3. Content

6.5. Universal Analytics vs. Google Analytics 4

6.5.1. Differences UA vs. GA4
6.5.2. Advantages and Limitations
6.5.3. Use of UA and GA4 Tools

6.6. Setting up Google Analytics

6.6.1. Installation and Integration
6.6.2. Universal Analytics Structure: Accounts, Properties and Views
6.6.3. Conversion Goals and Funnels

6.7. Reports

6.7.1. Real-Time Analytics
6.7.2. Audience Analytics
6.7.3. Purchase Analytics
6.7.4. Behavior Analytics
6.7.5. Conversion Analytics

6.8. Advanced Reports

6.8.1. Panels
6.8.2. Personalized Reports
6.8.3. APIs

6.9. Segments

6.9.1. Difference between Segment and Filter
6.9.2. Types of Segments: Predefined/Customized
6.9.3. Remarketing

6.10. Digital Analytics

6.10.1. Measurement
6.10.2. Implementation
6.10.3. Conclusions

Module 7. Data Management

7.1. Statistics

7.1.1. Statistics: Descriptive Statistics, Statistical Inferences 
7.1.2. Population, Sample, Individual 
7.1.3. Variables: Definition, Measurement Scales 

7.2. Types of Data Statistics 

7.2.1. According to Type

7.2.1.1. Quantitative: Continuous Data and Discrete Data
7.2.1.2. Qualitative: Binomial Data, Nominal Data and Ordinal Data 

7.2.2. According to Its Form: Numerical, Text, Logical
7.2.3. According to Their Source: Primary, Secondary

7.3. Data Management Planning

7.3.1. Definition of Objectives
7.3.2. Determination of Available Resources
7.3.3. Establishment of Time Lapses
7.3.4. Data Structure

7.4. Data Collection

7.4.1. Methodology of Data Collection
7.4.2. Data Collection Tools
7.4.3. Data Collection Channels

7.5. Data Cleaning 

7.5.1. Phases of Data Cleansing
7.5.2. Data Quality
7.5.3. Data Manipulation (with R)

7.6. Data Analysis, Interpretation and Evaluation of Results 

7.6.1. Statistical Measures
7.6.2. Relationship Indexes
7.6.3. Data Mining

7.7. Data Visualization 

7.7.1. Suitable Display According to Data Type
7.7.2. End-User Considerations
7.7.3. Executive Models of Results Presentation

7.8. Data Warehouse 

7.8.1. Elements that Comprise it
7.8.2. Design
7.8.3. Aspects to Consider

7.9. Data Availability  

7.9.1. Access
7.9.2. Uses
7.9.3. Security/Safety

7.10. Practical Applications 

7.10.1. Data Exploration
7.10.2. Manipulation and Adjustment of Patterns and Structures
7.10.3. Test Application and Modeling

Module 8. Data Protection 

8.1. Data Protection Regulations 

8.1.1. Regulatory Framework 
8.1.2. Definitions 
8.1.3. Subjects Obliged to Comply with the Regulations 

8.1.3.1. Differences between Controllers, Joint Controllers and Processors 

8.1.4. Data Protection Officer

8.2. Harmonized Regulation of Artificial Intelligence: Proposal for a European Regulation 

8.2.1. Prohibited Practices 
8.2.2. High-Risk Artificial Intelligence Systems 
8.2.3. Innovation Support Measures 

8.3. Principles Relating to the Processing of Personal Data 

8.3.1. Fairness, Loyalty and Transparency 
8.3.2. Purpose Limitation 
8.3.3. Data Minimization, Accuracy and Limitation of Retention Period 
8.3.4. Integrity and Confidentiality 
8.3.5. Proactive Responsibility 

8.4. Basis of Lawfulness or Legitimacy and Authorizations for the Processing, Including, if Applicable, the Communication of the Data

8.4.1. Consent 
8.4.2. Contractual Relationship or Pre-Contractual Measures 
8.4.3. Fulfillment of a Legal Obligation 
8.4.4. Protection of Vital Interests of the Data Subject or Another Person 
8.4.5. Public Interest or Exercise of Public Powers 
8.4.6. Legitimate Interest: Weighing of interests 

8.5. Individuals Rights

8.5.1. Transparency and Information 
8.5.2. Access 
8.5.3. Rectification and Deletion (Right to be Forgotten), Limitation and Portability 
8.5.4. Opposition and Automated Individual Decisions 
8.5.5. Limits to Rights 

8.6. Data Protection by Design: Analysis and Management of Personal Data Processing Risks  

8.6.1. Identification of Risks and Threats to the Rights and Freedoms of Individuals 
8.6.2. Risk Assessment 
8.6.3. Risk Management Plan 

8.7. Techniques for Ensuring Compliance with Data Protection Regulations 

8.7.1. Identification of Proactive Accountability Measures 
8.7.2. Organizational Measures 
8.7.3. Technical Measures 
8.7.4. The Register of Processing Activities 
8.7.5. Security Breach Management 
8.7.6. Codes of Conduct and Certifications 

8.8. The Data Protection Impact Assessment (DPA or DPIA) 

8.8.1. EIPD Needs Assessment 
8.8.2. Evaluation Methodology 
8.8.3. Identification of Risks and Threats 
8.8.4. Prior Consultation with the Supervisory Authority 

8.9. Contractual Regulation between Those Responsible, Those in charge and, Where Applicable, Other Subjects. International Data Transfers 

8.9.1. Data Access or Data Processing Contract 
8.9.2. Contracts between Co-Responsible Parties
8.9.3. Responsibilities of the Parties 
8.9.4. Definition and Safeguards to be Adopted in International Transfers 

8.10. Control Authorities. Violations and Penalties 

8.10.1. Violations 
8.10.2. Fines 
8.10.3. Penalty Procedure 
8.10.4. Control Authorities and Cooperation Mechanisms 

Module 9. Strategies and Applications 

9.1. Financial Services

9.1.1. The Implications of Artificial Intelligence (AI) in Financial Services. Opportunities and Challenges 
9.1.2. Case Uses 
9.1.3. Potential Risks Related to the Use of AI
9.1.4. Potential Future Developments/Uses of AI

9.2. Implications of Artificial Intelligence in the Healthcare Service 

9.2.1.Implications of AI in the Healthcare Sector. Opportunities and Challenges 
9.2.2. Case Uses

9.3. Risks Related to the Use of AI in the Health Service

9.3.1. Potential Risks Related to the Use of AI
9.3.2. Potential Future Developments/Uses of AI 

9.4. Retail 

9.4.1. Implications of AI in Retail. Opportunities and Challenges 
9.4.2. Case Uses 
9.4.3. Potential Risks Related to the Use of AI 
9.4.4. Potential Future Developments/Uses of AI

9.5. Industry 4.0 

9.5.1. Implications of AI in the 4.0 Industry. Opportunities and Challenges
9.5.2. Case Uses

9.6. Potential Risks Related to the use of AI in the 4.0 Industry 

9.6.1. Case Uses
9.6.2. Potential Risks Related to the Use of AI
9.6.3. Potential Future Developments/Uses of AI 

9.7. Public Administration. 

9.7.1. Implications of AI in Public Administration: Opportunities and Challenges
9.7.2. Case Uses 
9.7.3. Potential Risks Related to the Use of AI 
9.7.4. Potential Future Developments/Uses of AI 

9.8. Education 

9.8.1. Implications of AI in Educational: Opportunities and Challenges
9.8.2. Case Uses 
9.8.3. Potential Risks Related to the Use of AI 
9.8.4. Potential Future Developments/Uses of AI

9.9. Forestry and Agriculture 

9.9.1. Implications of AI in Forestry and Agriculture. Opportunities and Challenges 
9.9.2. Case Uses
9.9.3. Potential Risks Related to the Use of AI
9.9.4. Potential Future Developments/Uses of AI 

9.10. Human Resources 

9.10.1. Implications of AI for Human Resources Opportunities and Challenges
9.10.2. Case Uses 
9.10.3. Potential Risks Related to the Use of AI 
9.10.4. Potential Future Developments/Uses of AI 

Module 10. Optimization of the Company's Human Capital 

10.1. Human Capital in the Company

10.1.1. Value of Human Capital in the Technological World 
10.1.2. Managerial Skills 
10.1.3. Paradigm Shift in Management Models

10.2. Manager's Skills 

10.2.1. Management Process
10.2.2. Management Functions
10.2.3. Group Leadership Management in Companies: Group Relations

10.3. Communication in the Company 

10.3.1. The Company's Communication Process 
10.3.2. Interpersonal Relations in the Company 
10.3.3. Communication Techniques for Change 

10.3.3.1. Storytelling 
10.3.3.2. Assertive Communication Techniques. Feedback, Consensus

10.4. Business Coaching 

10.4.1. Business Coaching
10.4.2. The Practice of Coaching
10.4.3. Types of Coaching and Coaching in Organizations

10.4.3.1. Coaching as a Leadership Style

10.5. Business Mentoring

10.5.1. Mentoring in the Company 
10.5.2. The 4 Processes of a Mentoring Program
10.5.3. Benefits of this Business Tool 

10.6. Mediation and Conflict Resolution in the Company 

10.6.1. The Conflicts
10.6.2. Preventing, Addressing and Resolving Conflict
10.6.3. Stress and Work Motivation

10.7. Negotiation Techniques 

10.7.1. Negotiation at the Managerial Level in Technology Companies
10.7.2. Strategies and Main Types of Negotiation
10.7.3. The Figure of the Negotiator

10.8. Enterprise Change Management

10.8.1. Factors of Organizational Change 
10.8.2. Strategic Planning 
10.8.3. Organizational Change Management 

10.8.3.1. For Intangible Change: Teams, Communication, Culture, Leadership 
10.8.3.2. For basic or Tangible Change: Goal Setting, Performance Measurement, Learning, Recognition and Rewards 

10.9. Techniques for Improving Equipment Performance

10.9.1. Teamwork Techniques
10.9.2. Delegating in Work Teams

10.10. Group Dynamics. Classification 

10.10.1. The Role of the Dynamizer
10.10.2. Group Dynamics Techniques

10.10.2.1. Brainstorming+
10.10.2.2. Philps 6/6
10.10.2.3. Hot Air Balloon D

Module 11. Leadership, Ethics and Social Responsibility in Companies 

11.1. Globalization and Governance

11.1.1. Governance and Corporate Governance
11.1.2. The Fundamentals of Corporate Governance in Companies
11.1.3. The Role of the Board of Directors in the Corporate Governance Framework

11.2. Leadership

11.2.1. Leadership. A Conceptual Approach
11.2.2. Leadership in Companies
11.2.3. The Importance of Leaders in Business Management

11.3. Cross-Cultural Management

11.3.1. Concept of Cross-Cultural Management
11.3.2. Contributions to the Knowledge of National Cultures
11.3.3. Diversity Management

11.4. Management and Leadership Development

11.4.1. Concept of Management Development
11.4.2. Concept of Leadership
11.4.3. Leadership Theories
11.4.4. Leadership Styles
11.4.5. Intelligence in Leadership
11.4.6. The Challenges of Today's Leader

11.5. Business Ethics

11.5.1. Ethics and Morality
11.5.2. Business Ethics
11.5.3. Leadership and Ethics in Companies

11.6. Sustainability

11.6.1. Sustainability and Sustainable Development
11.6.2. The 2030 Agenda
11.6.3. Sustainable Companies

11.7. Corporate Social Responsibility

11.7.1. International Dimensions of Corporate Social Responsibility
11.7.2. Implementing Corporate Social Responsibility
11.7.3. The Impact and Measurement of Corporate Social Responsibility

11.8. Responsible Management Systems and Tools

11.8.1. CSR: Corporate Social Responsibility
11.8.2. Essential Aspects for Implementing a Responsible Management Strategy
11.8.3. Steps for the Implementation of a Corporate Social Responsibility Management System
11.8.4. Tools and Standards of CSR

11.9. Multinationals and Human Rights

11.9.1. Globalization, Multinational Corporations and Human Rights
11.9.2. Multinational Corporations and International Law
11.9.3. Legal Instruments for Multinationals in the Field of Human Rights

11.10. Legal Environment and Corporate Governance

11.10.1. International Rules on Importation and Exportation
11.10.2. Intellectual and Industrial Property
11.10.3. International Labor Law

Module 12. People and Talent Management

12.1. Strategic People Management

12.1.1. Strategic Human Resources Management
12.1.2. Strategic People Management

12.2. Human Resources Management by Competencies

12.2.1. Analysis of the Potential
12.2.2. Remuneration Policy
12.2.3. Career/Succession Planning

12.3. Performance Evaluation and Compliance Management

12.3.1. Performance Management
12.3.2. Performance Management: Objectives and Process

12.4. Innovation in Talent and People Management

12.4.1. Strategic Talent Management Models
12.4.2. Identification, Training and Development of Talent
12.4.3. Loyalty and Retention
12.4.4. Proactivity and Innovation

12.5. Motivation

12.5.1. The Nature of Motivation
12.5.2. Expectations Theory
12.5.3. Needs Theory
12.5.4. Motivation and Financial Compensation

12.6. Developing High Performance Teams

12.6.1. High-Performance Teams: Self-Managing Teams
12.6.2. Methodologies for Managing High Performance Self-Managed Teams

12.7. Productivity, Attraction, Retention and Activation of Talent

12.7.1. Productivity
12.7.2. Talent Attraction and Retention Levers

Module 13. Economic and Financial Management

13.1. Economic Environment

13.1.1. Macroeconomic Environment and the National Financial System
13.1.2. Financial Institutions
13.1.3. Financial Markets
13.1.4. Financial Assets
13.1.5. Other Financial Sector Entities

13.2. Executive Accounting

13.2.1. Basic Concepts
13.2.2. The Company's Assets
13.2.3. The Company's Liabilities
13.2.4. The Company's Net Worth
13.2.5. The Income Statement

13.3. Information Systems and Business Intelligence

13.3.1. Fundamentals and Classification
13.3.2. Cost Allocation Phases and Methods
13.3.3. Choice of Cost Center and Impact

13.4. Budget and Management Control

13.4.1. The Budgetary Model
13.4.2. The Capital Budget
13.4.3. The Operating Budget
13.4.5. The Cash Budget
13.4.6. Budget Monitoring

13.5. Financial Management

13.5.1. The Company's Financial Decisions
13.5.2. The Financial Department
13.5.3. Cash Surpluses
13.5.4. Risks Associated with Financial Management
13.5.5. Risk Management of the Financial Management

13.6. Financial Planning

13.6.1. Definition of Financial Planning
13.6.2. Actions to Be Taken in Financial Planning
13.6.3. Creation and Establishment of the Business Strategy
13.6.4. The Cash Flow Chart
13.6.5. The Working Capital Chart

13.7. Corporate Financial Strategy

13.7.1. Corporate Strategy and Sources of Financing
13.7.2. Corporate Financing Financial Products

13.8. Strategic Financing

13.8.1. Self-financing
13.8.2. Increase in Shareholder's Equity
13.8.3. Hybrid Resources
13.8.4. Financing through Intermediaries

13.9. Financial Analysis and Planning

13.9.1. Analysis of the Balance Sheet
13.9.2. Analysis of the Income Statement
13.9.3. Profitability Analysis

13.10. Analyzing and Solving Cases/Problems

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

Module 14. Commercial Management and Strategic Marketing 

14.1. Commercial Management

14.1.1. Conceptual Framework of Commercial Management
14.1.2. Commercial Strategy and Planning
14.1.3. The Role of Sales Managers

14.2. Marketing

14.2.1. The Concept of Marketing
14.2.2. The Basic Elements of Marketing
14.2.3. Marketing Activities in Companies

14.3. Strategic Marketing Management

14.3.1. The Concept of Strategic Marketing
14.3.2. Concept of Strategic Marketing Planning
14.3.3. Stages in the Process of Strategic Marketing Planning

14.4. Digital Marketing and e-Commerce

14.4.1. Objectives of Digital Marketing and e-Commerce
14.4.2. Digital Marketing and the Media It Uses
14.4.3. E-Commerce. General Context
14.4.4. Categories of e-Commerce
14.4.5. Advantages and Disadvantages of e-Commerce Compared to Traditional Commerce

14.5. Digital Marketing to Reinforce a Brand

14.5.1. Online Strategies to Improve Brand Reputation
14.5.2. Branded Content and Storytelling

14.6. Digital Marketing to Attract and Retain Customers

14.6.1. Loyalty and Engagement Strategies Using the Internet
14.6.2. Visitor Relationship Management
14.6.3. Hypersegmentation

14.7. Digital Campaign Management

14.7.1. What Is a Digital Advertising Campaign?
14.7.2. Steps to Launch an Online Marketing Campaign
14.7.3. Mistakes in Digital Advertising Campaigns

14.8. Sales Strategy

14.8.1. Sales Strategy
14.8.2. Sales Methods

14.9. Corporate Communication

14.9.1. Concept
14.9.2. The Importance of Communication in the Organization
14.9.3. Type of Communication in the Organization
14.9.4. Functions of Communication in the Organization
14.9.5. Elements of Communication
14.9.6. Problems of Communication
14.9.7. Communication Scenarios

14.10. Digital Communication and Reputation

14.10.1. Online Reputation
14.10.2. How to Measure Digital Reputation?
14.10.3. Online Reputation Tools
14.10.4. Online Reputation Report
14.10.5. Online Branding

Module 15. Executive Management

15.1. General Management

15.1.1. The Concept of General Management
15.1.2. The Role of the CEO
15.1.3. The CEO and their Responsibilities
15.1.4. Transforming the Work of Management

15.2. Operations Management

15.2.1. The Importance of Management
15.2.2. Value Chain
15.2.3. Quality Management

15.3. Public Speaking and Spokesperson Education

15.3.1. Interpersonal Communication
15.3.2. Communication Skills and Influence
15.3.3. Communication Barriers

15.4. Personal and Organizational Communication Tools

15.4.1. Interpersonal Communication
15.4.2. Interpersonal Communication Tools
15.4.3. Communication in the Organization
15.4.4. Tools in the Organization

15.5. Communication in Crisis Situations

15.5.1. Crisis
15.5.2. Phases of the Crisis
15.5.3. Messages: Contents and Moments

15.6. Preparation of a Crisis Plan

15.6.1. Analysis of Possible Problems
15.6.2. Planning
15.6.3. Adequacy of Personnel

15.7. Emotional Intelligence

15.7.1. Emotional Intelligence and Communication
15.7.2. Assertiveness, Empathy, and Active Listening
15.7.3. Self- Esteem and Emotional Communication

15.8. Personal Branding

15.8.1. Strategies for Personal Brand Development
15.8.2. Personal Branding Laws
15.8.3. Tools for Creating Personal Brands

15.9. Leadership and Team Management

15.9.1. Leadership and Leadership Styles
15.9.2. Leadership Skills and Challenges
15.9.3. Managing Change Processes
15.9.4. Managing Multicultural Teams

 The teaching materials of this program, elaborated by these specialists, have contents that are completely applicable to your professional experiences"