Learn about the main Business Intelligence tools that can be applied in the Marketing department and become a successful manager"

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 centre 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. 

Show the world your talent after completing this program. 

Multicultural Context

While studying at TECH, students will enjoy a unique experience by studying in a multicultural context. In a program with a global vision, through which students 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 students represent more than 200 different nationalities. 

Learn with the best

In the classroom, TECH’s 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. 

Teachers representing 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 Re-learning 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.      

Economy of Scale

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" 

TECH has designed a curriculum on Marketing Management and Business Intelligence of high academic level, specifically for business professionals, who are looking to take high-level programs to improve their qualifications and achieve the job improvement they desire. For this purpose, the syllabus has been structured according to the most relevant concepts of this field of study, which will undoubtedly be a great support for your learning, especially for being able to combine the theoretical part with a multitude of practical cases that will facilitate your study. 

The structure of this syllabus has been designed to allow students to self-direct their learning"   

Syllabus

This Advanced master’s degree in Senior Marketing Management, Business Intelligence Expert of TECH Global University is an intensive program that prepares students to face challenges and business decisions both nationally and internationally. Its content is designed to promote the development of managerial skills that enable more rigorous decision-making in uncertain environments.  

Throughout 3.000 hours of study, students will analyze a multitude of practical cases through individual work, achieving high quality learning that can be applied to their daily practice. It is, therefore, an authentic immersion in real business situations.   

This program deals in depth with the main areas of the company and is designed for managers to understand marketing management and business intelligence from a strategic, international and innovative perspective. 

A plan designed for students, focused on their professional improvement and that prepares them to achieve excellence in the field of marketing and business management. A program that understands your needs and those of your company through innovative content based on the latest trends, and supported by the best educational methodology and an exceptional faculty, which will provide you with the competencies to solve critical situations in a creative and efficient way.  

This program takes place over 24 months and is divided into 24 modules:  

Module 1 Management and Leadership
Module 2 Logistics and Economic Management  
Module 3 Strategy in Marketing Management 
Module 4 Operational Marketing
Module 5 Customer Relationship Management  
Module 6 Sectorial Marketing 
Module 7 International Marketing  
Module 8 Digital Marketing and E-Commerce  
Module 9 E-Commerce and Shopify  
Module 10 Social Media and Community Management 
Module 11 Introduction to Market Research
Module 12 Qualitative Research Techniques 
Module 13 Quantitative Research Techniques 
Module 14 Market Research Production 
Module 15 Analysis of Results and Market Research Applications
Module 16 Enterprise Business Intelligence 
Module 17 Business Perspective  
Module 18 Data-driven business transformation  
Module 19 Viewing Data  
Module 20 Programming for data analysis  
Module 21 Data management  
Module 22 Data Protection 
Module 23 Business Intelligence and Artificial Intelligence Strategies and applications 
Module 24 Optimization of the company's human capital

Where, When and How is it Taught?

TECH offers students to the possibility of developing this program completely online. During the 24 months of training, will be able to access all the contents of this program at any time, which will allow the student to self-manage study time. 

Module 1. Management and Leadership

1.1. General Management 

1.1.1. Integrating Functional Strategies into the Global Business Strategies
1.1.2. Management Policy and Processes
1.1.3. Society and Enterprise

1.2. Strategic Management

1.2.1. Establish the Strategic Position: Mission, Vision and Values
1.2.2. Developing New Businesses
1.2.3. Growing and Consolidating Companies

1.3. Competitive Strategy 

1.3.1. Market Analysis
1.3.2. Sustainable Competitive Advantage
1.3.3. Return on Investment

1.4. Corporate Strategy 

1.4.1. Driving Corporate Strategy
1.4.2. Pacing Corporate Strategy
1.4.3. Framing Corporate Strategy

1.5. Planning and Strategy 

1.5.1. The Relevance of Strategic Direction in the Management Control Process
1.5.2. Analysis of the Environment and the Organization
1.5.3. Lean Management

1.6. Talent Management

1.6.1. Managing Human Capital
1.6.2. Environment, Strategy, and Metrics
1.6.3. Innovation in People Management

1.7. Management and Leadership Development 

1.7.1. Leadership and Leadership Styles
1.7.2. Motivation
1.7.3. Emotional Intelligence
1.7.4. Skills and Abilities of the Leader 2.0
1.7.5. Efficient Meetings

1.8. Change Management 

1.8.1. Performance Analysis
1.8.2. Leading Change. Resistance to Change
1.8.3. Managing Change Processes
1.8.4. Managing Multicultural Teams

Module 2. Logistics and Economic Management  

2.1. Financial Diagnosis

2.1.1. Indicators for Analyzing Financial Statements
2.1.2. Profitability Analysis
2.1.3. Economic and Financial Profitability of a Company

2.2. Economic Analysis of Decisions 

2.2.1. Budget Control
2.2.2. Competitive Analysis. Comparative Analysis
2.2.3. Decision-Making. Business Investment or Divestment

2.3. Investment Valuation and Portfolio Management 

2.3.1. Profitability of Investment Projects and Value Creation
2.3.2. Models for Evaluating Investment Projects
2.3.3. Sensitivity Analysis, Scenario Development, and Decision Trees

2.4. Purchasing Logistics Management

2.4.1. Stock Management
2.4.2. Warehouse Management
2.4.3. Purchasing and Procurement Management

2.5. Supply Chain Management

2.5.1. Costs and Efficiency of the Operations Chain
2.5.2. Change in Demand Patterns
2.5.3. Change in Operations Strategy

2.6. Logistical Processes

2.6.1. Organization and Management by Processes
2.6.2. Procurement, Production and Distribution
2.6.3. Quality, Quality Costs, and Tools
2.6.4. After-Sales Service

2.7. Logistics and Customers

2.7.1. Demand Analysis and Forecasting
2.7.2. Sales Forecasting and Planning
2.7.3. Collaborative Planning, Forecasting, and Replacement

2.8. International Logistics

2.8.1. Customs, Export and Import processes
2.8.2. Methods and Means of International Payment
2.8.3. International Logistics Platforms

Module 3. Strategy in Marketing Management 

3.1. Marketing Management

3.1.1. Positioning and Value Creation
3.1.2. Company's Marketing Orientation and Positioning
3.1.3. Strategic Marketing vs. Operational Marketing
3.1.4. Objectives in Marketing Management
3.1.5. Integrated Marketing Communications

3.2. The Function of Strategic Marketing

3.2.1. Main Marketing Strategies
3.2.2. Segmentation, Targeting, and Positioning
3.2.3. Managing Strategic Marketing

3.3. Marketing Strategy Dimensions

3.3.1. Necessary Resources and Investments
3.3.2. Fundamentals of Competitive Advantage
3.3.3. The Company’s Competitive Behavior
3.3.4. Focus Marketing

3.4. New Product Strategy Development

3.4.1. Creativity and Innovation in Marketing
3.4.2. Generation and Filtering of Ideas
3.4.3. Commercial Viability Analysis
3.4.4. Development, Market Testing, and Commercialization

3.5. Pricing Policies

3.5.1. Short and Long-Term Aims
3.5.2. Types of Pricing
3.5.3. Factors that Affect Pricing

3.6. Promotion and Merchandising Strategies

3.6.1. Advertising Management
3.6.2. Communication and Media Plan
3.6.3. Merchandising as a Marketing Technique
3.6.4. Visual Merchandising

3.7. Distribution, Expansion, and Intermediation Strategies

3.7.1. Outsourcing of Sales Force and Customer Service
3.7.2. Commercial Logistics in Product and Service Sales Management
3.7.3. Sales Cycle Management

3.8. Developing the Marketing Plan

3.8.1. Analysis and Diagnosis
3.8.2. Strategic Decisions
3.8.3. Operational Decisions

Module 4. Operational Marketing

4.1. Marketing Mix

4.1.1. The Marketing Value Proposition
4.1.2. Marketing Mix Policies, Strategies, and Tactics
4.1.3. Elements of Marketing Mix
4.1.4. Customer Satisfaction and Marketing Mix

4.2. Product Management 

4.2.1. Consumption Distribution and Product Life Cycle
4.2.2. Obsolescence, Expiration and Periodic Campaigns
4.2.3. Order Management and Inventory Control Ratios

4.3. Pricing Principles

4.3.1. Analysis of the environment
4.3.2. Production Costs and Discount Margins
4.3.3. Final Price and Positioning Map

4.4. Distribution Channel Management

4.4.1. Trade Marketing
4.4.2. Distribution Culture and Competition
4.4.3. Designing and Managing Channels
4.4.4. Functions of Distribution Channels
4.4.5. Route to Market

4.5. Promotion and Sales Channels

4.5.1. Corporate Branding
4.5.2. Advertising
4.5.3. Sales Promotion
4.5.4. Public Relations and Personal Selling
4.5.5. Street Marketing

4.6. Branding

4.6.1. Brand Evolution
4.6.2. Creating and Developing a Successful Brand
4.6.3. Brand Equity
4.6.4. Category Management

4.7. Managing Marketing Groups

4.7.1. Work Teams and Meeting Management
4.7.2. Coaching and Team Management
4.7.3. Managing Equality and Diversity

4.8. Communication and Marketing

4.8.1. Communication Integrated into Marketing
4.8.2. Designing a Marketing Communication Program 
4.8.3. Communication Skills and Influence
4.8.4. Barriers to Business Communication

Module 5. Customer Relationship Management  

5.1. Knowing the Market and the Consumer

5.1.1. Open Innovation
5.1.2. Competitive Intelligence
5.1.3. Sharing Economy

5.2. CRM and Business Philosophy

5.2.1. Business Philosophy or Strategic Orientation
5.2.2. Customer Identification and Differentiation
5.2.3. The Company and its Stakeholders
5.2.4. Clienting 

5.3. Database Marketing and Customer Relationship Management

5.3.1. Database Marketing Applications
5.3.2. Laws and Regulations
5.3.3. Information Sources, Storage, and Processing

5.4. Consumer Psychology and Behavior

5.4.1. The Study of Consumer Behavior
5.4.2. Internal and External Consumer Factors
5.4.3. Consumer Decision Process
5.4.4. Consumerism, Society, Marketing, and Ethics

5.5. Areas of CRM Management

5.5.1. Customer Service
5.5.2. Managing the Sales Force
5.5.3. Customer Service

5.6. Consumer Centric Marketing

5.6.1. Segmentation
5.6.2. Profitability Analysis
5.6.3. Customer Loyalty Strategies

5.7. CRM Management Techniques

5.7.1. Direct Marketing
5.7.2. Multichannel Integration
5.7.3. Viral Marketing

5.8. Advantages and Risks of Implementing CRM

5.8.1. CRM, Sales and Costs
5.8.2. Customer Satisfaction and Loyalty
5.8.3. Technology Implementation
5.8.4. Strategic and Management Errors

Module 6. Sectorial Marketing 

6.1. Services Marketing

6.1.1. Evolution and Growth of the Service Sector
6.1.2. Function of Services Marketing
6.1.3. Marketing Strategy in the Service Sector

6.2. Touristic Marketing

6.2.1. Features of the Tourism Sector
6.2.2. Tourist Product
6.2.3. The Customer in Tourism Marketing

6.3. Political and Electoral Marketing

6.3.1. Political Marketing vs. Election Marketing
6.3.2. Political Market Segmentation
6.3.3. Electoral Campaign

6.4. Social Marketing and Responsible Marketing

6.4.1. Social Cause Marketing and CSR
6.4.2. Environmental Marketing
6.4.3. Segmentation in Social Marketing

6.5. Retail Management

6.5.1. Relevance
6.5.2. Reward
6.5.3. Cost Reduction
6.5.4. Relationship with the Customer

6.6. Banking Marketing

6.6.1. State Regulation
6.6.2. Branches and Segmentation
6.6.3. Inbound Marketing in the Banking Sector

6.7. Health Services Marketing

6.7.1. Internal Marketing
6.7.2. User Satisfaction Studies
6.7.3. Market-Oriented Quality Management

6.8. Sensory Marketing 

6.8.1. Shopping Experience as a Sensory Experience
6.8.2. Neuromarketing and Sensory Marketing
6.8.3. Arrangement and Presentation of the Point of Sale

Module 7. International Marketing  

7.1. International Market Research

7.1.1. Emerging Markets Marketing
7.1.2. PES Analysis
7.1.3. What, How, and Where to Export?
7.1.4. International Marketing-Mix Strategies

7.2. International Segmentation

7.2.1. Criteria for Market Segmentation at the International Level
7.2.2. Market Niches
7.2.3. International Segmentation Strategies

7.3. International Positioning

7.3.1. Branding in International Markets
7.3.2. Positioning Strategies in International Markets
7.3.3. Global, Regional, and Local Brands

7.4. Product Strategies in International Markets

7.4.1. Product Modification, Adaptation, and Diversification
7.4.2. Global Standardized Products
7.4.3. The Product Portfolio

7.5. Prices and Exports

7.5.1. Export Prices Calculation
7.5.2. Incoterms
7.5.3. International Price Strategy

7.6. Quality in International Marketing

7.6.1. Quality and International Marketing
7.6.2. Standards and Certifications
7.6.3. CE Marking

7.7. International Promotion

7.7.1. The International Promotion MIX
7.7.2. Advertising
7.7.3. International Fairs
7.7.4. Country Branding

7.8. Distribution through International Channels

7.8.1. Channel and Trade Marketing
7.8.2. Export Consortiums
7.8.3. Types of Exports and Foreign Trade

Module 8. Digital Marketing and E-Commerce  

8.1. Digital Marketing and E-Commerce

8.1.1. The Digital Economy and the Sharing Economy
8.1.2. Trends and Social Changes in Consumers
8.1.3. Digital Transformation of Traditional Companies
8.1.4. The Roles of the Chief Digital Officer

8.2. Digital Strategy

8.2.1. Segmentation and Positioning in the Competitive Context
8.2.2. New Marketing Strategies for Products and Services
8.2.3. From Innovation to Cash Flow

8.3. Technology Strategy

8.3.1. Web Development
8.3.2. Hosting and Cloud Computing
8.3.3. Content Management Systems (CMS)
8.3.4. Formats and Digital Media
8.3.5. Technological e-Commerce Platforms

8.4. Digital Regulation

8.4.1. Privacy Policy and Personal Data Protection Act
8.4.2. Fake Profiles and Fake Followers
8.4.3. Legal Aspects of Marketing, Advertising, and Digital Content

8.5. Online Market Research

8.5.1. Quantitative Research Tools in Online Markets
8.5.2. Dynamic Qualitative Customer Research Tools

8.6. Online Agencies, Media, and Channels

8.6.1. Integral, Creative, and Online Agencies
8.6.2. Traditional and New Media
8.6.3. Online Channels
8.6.4. Other Digital Players

Module 9. E-Commerce and Shopify  

9.1. Digital E-Commerce Management

9.1.1. New E-Commerce Business Models
9.1.2. Planning and Developing an E-Commerce Strategic Plan
9.1.3. Technological Structure in E-Commerce

9.2. E-Commerce Operations and Logistics

9.2.1. How to Manage Fulfillment
9.2.2. Digital Point-of-Sale Management
9.2.3. Contact Center Management
9.2.4. Automation in Management and Monitoring Processes

9.3. Implementing E-Commerce Techniques

9.3.1. Social Media and Integration in the E-Commerce Plan
9.3.2. Multichannel Strategy
9.3.3. Personalizing Dashboards

9.4. Digital Pricing

9.4.1. Online Payment Methods and Payment Gateways
9.4.2. Electronic Promotions
9.4.3. Digital Price Timing
9.4.4. E-Auctions

9.5. From E-Commerce to M-Commerce and S-Commerce

9.5.1. E-Marketplace Business Models
9.5.2. S-Commerce and Brand Experience
9.5.3. Purchase via Mobile Devices

9.6. Customer Intelligence: from E-CRM to S-CRM

9.6.1. Integrating the Consumer in the Value Chain
9.6.2. Online Research and Loyalty Techniques
9.6.3. Planning a Customer Relationship Management Strategy

9.7. Digital Marketing Trade

9.7.1. Cross Merchandising
9.7.2. Designing and Managing Facebook Ads Campaigns
9.7.3. Designing and Managing Google Ad Campaigns

9.8. Online Marketing for E-Commerce

9.8.1. Inbound Marketing
9.8.2. Display and Programmatic Purchasing
9.8.3. Communication Plan

Module 10. Social Media and Community Management 

10.1. Web 2.0 or the Social Web

10.1.1. Organization in the Age of Conversation
10.1.2. Web 2.0 Is All About People
10.1.3. New Environments, New Content

10.2. Digital Communication and Reputation

10.2.1. Crisis Management and Online Corporate Reputation
10.2.2. Online Reputation Report
10.2.3. Netiquette and Good Practices on Social Media
10.2.4. Branding and Networking 2.0

10.3. General, Professional, and Microblogging Platforms

10.3.1. Facebook
10.3.2. LinkedIn
10.3.3. Google+
10.3.4. Twitter

10.4. Video, Image, and Mobility Platforms

10.4.1. YouTube
10.4.2. Instagram
10.4.3. Flickr
10.4.4. Vimeo
10.4.5. Pinterest

10.5. Corporate Blogging

10.5.1. How to Create a Blog
10.5.2. Content Marketing Strategy
10.5.3. How to Create a Content Plan for Your Blog
10.5.4. Content Curation Strategy

10.6. Social Media Strategies

10.6.1. Corporate Communication Plan 2.0
10.6.2. Corporate PR and Social Media
10.6.3. Analysis and Evaluation of Results

10.7. Community Management

10.7.1. Functions, Duties, and Responsibilities of the Community Management
10.7.2. Social Media Manager
10.7.3. Social Media Strategist

10.8. Social Media Plan

10.8.1. Designing a Social Media Plan
10.8.2. Defining the Strategy to Be Followed in Each Medium
10.8.3. Contingency Protocol in Case of Crisis

Module 11. Introduction to Market Research

11.1. Market Research Fundamentals

11.1.1. Concept of Marketing Research and Marketing   
11.1.2. Utility of Market Research  
11.1.3. Market Research Ethics

11.2. Applications of Market Research

11.2.1. The Value of Research for Managers  
11.2.2. Factors in the Decision to Investigate the Market 
11.2.3. Main objectives of Market Research 

11.3. Market Research Methods

11.3.1. Exploratory Research
11.3.2. Descriptive Research 
11.3.3. Causal Investigations 

11.4. Types of Information

11.4.1. Elaboration: Primary and Secondary 
11.4.2. Qualitative Nature 
11.4.3. Qualitative Nature  

11.5. Organisation of Market Research

11.5.1. In-House Market Research Department 
11.5.2. Research Outsourcing 
11.5.3. Decision Factors: Internal vs. External 

11.6. Research Project Management

11.6.1. Market Research as a Process 
11.6.2. Planning Stages in Market Research 
11.6.3. Stages of Market Research Implementation 
11.6.4. Managing a Research Project  

11.7. Cabinet Studies

11.7.1. Objectives of the Cabinet Studies 
11.7.2. Sources of Secondary Information 
11.7.3. Results of the Cabinet Studies 

11.8. Field Work

11.8.1. Obtaining Primary Information 
11.8.2. Organization of Information Gathering 
11.8.3. Interviewer Control  

11.9. Online Market Research

11.9.1. Quantitative Research Tools in Online Markets
11.9.2. Dynamic Qualitative Customer Research Tools

11.10. The Market Research Proposal 

11.10.1. Objectives and Methodology 
11.10.2. Deadlines for Delivery 
11.10.3. Budget 

Module 12. Qualitative Research Techniques 

12.1. Introduction to Qualitative Research

12.1.1. Objectives of Qualitative Research 
12.1.2. Sources of Qualitative Information 
12.1.3. Characteristics of Qualitative Information 

12.2. Group Dynamics

12.2.1. Concepts and Objectives  
12.2.2. Organization and Implementation 
12.2.3. Group Dynamics Results 

12.3. The In-Depth Interview

12.3.1. Concepts and Objectives  
12.3.2. The In-Depth Interview Process 
12.3.3. Application of the In-Depth Interviews  

12.4. Projective Techniques

12.4.1. Concepts and Objectives 
12.4.2. Main Projective Techniques 

12.5. Creativity Techniques

12.5.1. Concepts and Objectives  
12.5.2. Intuitive techniques: Brainstorming 
12.5.3. Formal techniques: Delphi Method 
12.5.4. Other Creativity Techniques 

12.6. Observation as a Qualitative Technique

12.6.1. Concept and Applications  
12.6.2. Observation Scenarios 
12.6.3. Technical Resources 
12.6.4. Assessment of the Observation 

12.7. Neuromarketing: The Responses of the Brain

12.7.1. Concept and Applications  
12.7.2. Observation Scenarios in Neuromarketing 
12.7.3. Neuromarketing Techniques 

12.8. Pseudo-Purchase

12.8.1. Concept and Applications  
12.8.2. Pseudo-Purchase Scenarios 
12.8.3. Mystery Shopper 

12.9. Digital Qualitative Research

12.9.1. Description and Characteristics   
12.9.2. Main Online Qualitative Techniques 

12.10. Application of Qualitative Research

12.10.1. Structure of Qualitative Research Results 
12.10.2. Projection of Qualitative Research Results 
12.10.3. Decision-Making Applications 

Module 13. Quantitative Research Techniques 

13.1. Introduction to Quantitative Research 

13.1.1. Quantitative Research Objectives 
13.1.2. Sources of Quantitative Information 
13.1.3. Characteristics of Quantitative Information 

13.2. The Personal Survey  

13.2.1. Concept and Characteristics  
13.2.2. Types of Personal Survey 
13.2.3. Advantages and Disadvantages of the Personal Survey 

13.3. The Telephone Survey 

13.3.1. Concept and Characteristics  
13.3.2. Types of Personal Survey 
13.3.3. Advantages and Disadvantages of the Personal Survey 

13.4. The Self-Administered Survey 

13.4.1. Concept and Characteristics 
13.4.2. Online Survey 
13.4.3. Postal and e-mail surveys 
13.4.4. Survey by Personal Delivery 

13.5. The Omnibus 

13.5.1. Concept and Characteristics 
13.5.2. Omnibus Results 
13.5.3. Types of Omnibuses 

13.6. Board 

13.6.1. Concept and Characteristics 
13.6.2. Panel Results 
13.6.3. Panel Types 

13.7. Tracking 

13.7.1. Concept and Characteristics 
13.7.2. Tracking Results 
13.7.3. Types of Tracking 

13.8. Observation as a Quantitative Technique 

13.8.1. Concept and Usefulness  
13.8.2. Observation Scenarios 
13.8.3. Technical Resources 
13.8.4. Results of Quantitative Observation 

13.9. Experimentation  

13.9.1. Concept and Characteristics 
13.9.2. Product testing 
13.9.3. Market Test 

13.10. Application of Quantitative Research 

13.10.1. Structure of Quantitative Research Results 
13.10.2. Projection of Quantitative Research Results 
13.10.3. Decision-Making Applications 

Module 14. Market Research Production 

14.1. The Quantitative Questionnaire  

14.1.1. Concept, Functions and Type I
14.1.2. Phases of the Questionnaire Design 
14.1.3. Structure of the Questionnaire

14.2. Formulation of Questions 

14.2.1. Types of Questions 
14.2.2. Hierarchization of Questions 
14.2.3. Pre-Test of the Questionnaire 

14.3. Scales of Measurement 

14.3.1. Purpose and Types of Scales 
14.3.2. Basic, Comparative and Non-Comparative Scales 
14.3.3. Creation and Evaluation of Scales 
14.3.4. Standardized Scales  

14.4. Internet Questionnaire Design 

14.4.1. Characteristics of the Online Questionnaire 
14.4.2. Online Questionnaire Structure 
14.4.3. Main Online Survey Supports 

14.5. Scripts and Qualitative Interviews 

14.5.1. Concept and Types  
14.5.2. Structure of Scripts and Interviews 
14.5.3. Formulation of Questions  

14.6. Sampling 

14.6.1. Sampling Concept and Process 
14.6.2. Quantitative Sampling Methods 
14.6.3. Sample Selection in Qualitative Research 

14.7. Probability Sampling 

14.7.1. Simple Sampling 
14.7.2. Stratified Sampling 
14.7.3. Cluster Sampling 

14.8. Non-probability Sampling 

14.8.1. Random Route 
14.8.2. Fees 
14.8.3. Availability 
14.8.4. Other Non-Probabilistic Methods 

14.9. Sample Size 

14.9.1. Sample Size Determining Factors 
14.9.2. Sample Size Calculation 
14.9.3. Sample Size in Industrial Markets 

14.10. Fieldwork Process 

14.10.1. Interviewer Training 
14.10.2. Coordination of Information Gathering 
14.10.3. Evaluation and Incidents 

Module 15. Analysis of Results and Market Research Applications

15.1. Information Analysis Plan 

15.1.1. Data Preparation 
15.1.2. Stages of the Analysis Plan 
15.1.3. Outline of the Analysis Plan 

15.2. Descriptive Analysis of Information 

15.2.1. Concept of Descriptive Analysis 
15.2.2. Types of Descriptive Analysis 
15.2.3. Statistical Programs in Descriptive Analysis 

15.3. Bivariate Analysis 

15.3.1. Hypothesis Contrast 
15.3.2. Types of Bivariate Analysis 
15.3.3. Statistical Programs in Bivariate Analysis

15.4. Multivariate Dependency Analysis 

15.4.1. Concept and Characteristics 
15.4.2. Types of Multivariate Dependency Analyses 

15.5. Multivariate Analysis of Interdependence 

15.5.1. Concept and Characteristics 
15.5.2. Types of Multivariate Interdependence Analyses 

15.6. Market Research Findings 

15.6.1. Differentiation of Information Analysis  
15.6.2. Joint Interpretation of Information 
15.6.3. Application of the Conclusions to the Object of the Research 

15.7. Creating a Report 

15.7.1. Concept, Utility and Types 
15.7.2. Structure of the Report 
15.7.3. Editorial Standards 

15.8. International Market Research  

15.8.1. Introduction to International Market Research 
15.8.2. International Market Research Process 
15.8.3. The Importance of Secondary Sources in International Research 

15.9. Feasibility Studies   

15.9.1. Obtaining Information on Purchasing Behavior and Motives 
15.9.2. Analysis and Evaluation of the Competitive Offer 
15.9.3. Market Structure and Potential 
15.9.4. Purchase Intention 
15.9.5. Feasibility Results 

15.10. Voting Intention Studies 

15.10.1. Pre-Election Studies 
15.10.2. Exit Polls 
15.10.3. Vote Estimates 

Module 16. Enterprise Business Intelligence 

16.1. Enterprise Business Intelligence  

16.1.1. The World of Data
16.1.2. Relevant Concepts
16.1.3. Main Characteristics
16.1.4. Solutions in Today's Market
16.1.5. Overall Architecture of a BI Solution
16.1.6. Cybersecurity in BI and Data Science

16.2. New Business Concept 

16.2.1. Why BI
16.2.2. Obtaining Information
16.2.3. BI in the Different Departments of the Company
16.2.4. Reasons to Invest in BI

16.3. Data Warehouse 

16.3.1. Definition and Objectives Data Warehouse and Data Mart
16.3.2. Architecture
16.3.3. Dimensional Modeling and its Types of Diagrams
16.3.4. Extraction, Transformation and Loading Process (ETL)
16.3.5. Metadata

16.4. Big Data and Data Capture

16.4.1. Capture
16.4.2. Transformation
16.4.3. Storage

16.5. Reporting Business Intelligence (BI)  

16.5.1. B.D. Structures
16.5.2. BB.DD. OLTP and OLAP
16.5.3. Examples

16.6. The Dashboards or Integral Control Panels 

16.6.1. Control Panels
16.6.2. Decision Support Systems
16.6.3. Executive Information Systems

16.7. Deep Learning 

16.7.1. Deep Learning
16.7.3. Deep Learning Applications

16.8. Machine Learning

16.8.1. Machine Learning  
16.8.2. Understand Machine Learning 
16.8.3. Deep Learning vs. Machine Learning 

16.9. BI Tools and Solutions

16.9.1. Choosing the Best Tool
16.9.2. Microsoft Power BI, MicroStrategy y Tableau
16.9.3. SAP BI, SAS BI and Qlikview
16.9.4. Prometheus

16.10. BI Project Planning and Management 

16.10.1. First Steps to define a BI project
16.10.2. BI Solution for Your Company
16.10.3. Requirements and Objectives

Module 17. Business Perspective  

17.1. The Company  

17.1.1. Venture Capital Theory
17.1.2. Organizational Morphology: Size, Shape, Activity and Sectors
17.1.3. Organization and Resources
17.1.4. Management and Their Needs

17.2. Company: Market and Customer

17.2.1. Market and Customer
17.2.2. Market Analysis and Segmentation
17.2.3. Direct and Indirect Competition
17.2.4. Competitive Advantage

17.3. DAFO Analysis

17.3.1. Business Strategy
17.3.2. DAFO Analysis
17.3.3. Objectives and Deadlines [SMART, C/M/L/P, Cascading Objectives]
17.3.4. Measuring Results: Knowing the Reality
17.3.5. Key Performance Indicators [KPI]

17.4. Information as an Asset

17.4.1. Information and Management
17.4.2. Life Cycle Information
17.4.3. Operational System and Strategic System

17.5. Balanced Scorecard

17.5.1. Operational, Tactical and Strategic Scorecards
17.5.2. CMI Definition
17.5.3. Financial Perspective
17.5.4. Customer Perspective
17.5.5. Internal Processes Perspective
17.5.6. Learning and Growth Perspective

17.6. Productivity Analysis 

17.6.1.  Income, Expenditures, Investment and Consumption
17.6.2. Cost Analysis and Allocation
17.6.3. ROI and other Ratios of interest

17.7. Distribution and Sales

17.7.1. Relevance of the Department
17.7.2. Channels and Equipment
17.7.3. Types of Sales and Consumption

17.8. Other Common Areas

17.8.1. Production and Service Delivery
17.8.2. Distribution and Logistics
17.8.3. Commercial Communication
17.8.4. Inbound Marketing

17.9. Data Management 

17.9.1. Roles and Responsibilities [Managerial Roles and Technical Roles]
17.9.2. Stakeholder Identification
17.9.3. Information Management Systems [Intro and Types, without Technology Details]
17.9.4. Type of Operating Systems
17.9.5. Strategic or Decision Support Systems
17.9.6. Platforms for information: Cloud Computing vs. On Premise

17.10. Exploring the Information

17.10.1. Intro SQL: Relational Databases Basic Concepts (DDL and DML, PK, FK, JOINS)  
17.10.2. Networks and Communications: Public/Private Networks, Network/Subnet/Router Address and DNS. VPN Tunnel and SSH. [concept intro]   
17.10.3. Operational System: Standardized Data Templates
17.10.4. Strategic System: Multidimensional Model [intro Because it is a Complete Topic by Rafaél], OLAP and Graphical Dashboards
17.10.5. Strategic Analysis of BB.DD. and Report Composition

Module 18. Data-driven business transformation  

18.1. Big Data 

18.1.1. Big Data in Enterprises
18.1.2. Concept of Value
18.1.3. Value Project Management

18.2. Customer Journey

18.2.1. Customer Life Cycle
18.2.2. Association of Campaigns to the Life Cycle
18.2.3. Campaign Metrics

18.3. Data Management for Campaigns

18.3.1. Datawarehouse and Datalab
18.3.2. Campaign Creation Tools
18.3.3. Drive Methods

18.4. Digital Marketing GDPR

18.4.1. Data Anonymization and Manipulation of Personal Data
18.4.2. Robinson Concept
18.4.3. Exclusion lists

18.5. Scorecard

18.5.1. KPIs 
18.5.2. Audience
18.5.3. Tools
18.5.4. Storytelling

18.6. Customer Analysis and Characterization

18.6.1. 360º Customer Vision
18.6.2. Relation of Analysis to Tactical Actions
18.6.3. Analysis Tools

18.7. Business Examples Applying Big Data Techniques 

18.7.1. Upselling/Cross-Selling
18.7.2. Propensity Models
18.7.3. Risk Models
18.7.4. Predictions
18.7.5. Image Processing

Module 19. Viewing Data  

19.1. Viewing Data 

19.1.1. Data visualization
19.1.2. Importance of Data Analysis and Visualization
19.1.3. Evolution

19.2. Design 

19.2.1. Use of Color
19.2.2. Composition and Typography
19.2.3. Recommendations

19.3. Types of Data

19.3.1. Qualitative
19.3.2. Quantitative
19.3.3. Temporary Data

19.4. Data Sets 

19.4.1. Files
19.4.2. Databases
19.4.3. Open Data
19.4.4. Streaming Data

19.5. Common Types of Representation 

19.5.1. Columns
19.5.2. Bars
19.5.3. Lines
19.5.4. Areas
19.5.5. Dispersion

19.6. Advanced Types of Representation 

19.6.1. Circulars
19.6.2. Rings
19.6.3. Bubbles
19.6.4. Maps

19.7. Application by Area 

19.7.1. Political Science and Sociology
19.7.2. Science
19.7.3. Marketing
19.7.4. Health and Well-being
19.7.5. Meteorology
19.7.6. Business and Finance

19.8. Storytelling 

19.8.1. Importance of Storytelling
19.8.2. Storytelling History
19.8.3. Application of Storytelling

19.9. Visualization Software 

19.9.1. Commercials
19.9.2. Free
19.9.3. Online
19.9.4. Free Software

19.10. The Future of Data Visualization 

19.10.1. Virtual Reality
19.10.2. Augmented Reality
19.10.3. Artificial Intelligence

Module 20. Programming for data analysis  

20.1. Programming for Data Analysis

20.1.1. Language for Data Analysis
20.1.2. Evolution and Characteristics of the Main Tools
20.1.3. Installation and Configuration

20.2. Types of Data

20.2.1. Basic Types
20.2.2. Complex Types
20.2.3. Other Structures

20.3. Structures and Operations

20.3.1. Data Operations
20.3.2. Control Structures
20.3.3. File Operations

20.4. Data Extraction and Analysis

20.4.1. Statistical Summaries
20.4.2. Univariate Analysis
20.4.3. Multivariate Analysis

20.5. Visualisation

20.5.1. Univariate Graphs
20.5.2. Multivariable Graphs
20.5.3. Other Charts of Interest

20.6. Pre-processing 

20.6.1. The Importance of Data Quality
20.6.2. Outlier Detection and Analysis
20.6.3. Other Dataset Quality Factors

20.7. Advanced Pre-processing

20.7.1. Subsampling
20.7.2. Resampling
20.7.3. Dimensionality Reduction

20.8. Data Modeling  

20.8.1. Modeling Phases
20.8.2. Division of the Data Set
20.8.3. Metrics for Prediction

20.9. Advanced Data Modeling 

20.9.1. Unsupervised Models
20.9.2. Supervised Models
20.9.3. Libraries for Modeling

20.10. Tools and Best Practices

20.10.1. Best Practices for Modeling
20.10.2. The Tools of a Data Analyst
20.10.3. Conclusion and Bookstores of Interest

Module 21. Data management  

21.1. Statistics

21.1.1. Statistics: Descriptive Statistics, Statistical Inferences
21.1.2. Population, Sample, Individual
21.1.3. Variables: Definition, Measurement Scales

21.2. Types of Data Statistics 

21.2.1. According to Type

21.2.1.1. Quantitative: Continuous Data and Discrete Data
21.2.1.2. Qualitative: Binomial Data, Nominal Data and Ordinal Data

21.2.2. According to Its Form: Numerical, Text, Logical
21.2.3. According to Their Source: Primary and Secondary

21.3. Data Management Planning

21.3.1. Definition of Objectives
21.3.2. Determination of Available Resources
21.3.3. Establishment of Time Lapses
21.3.4. Data Structure

21.4. Data Collection

21.4.1. Methodology of Data Collection
21.4.2. Data Collection Tools
21.4.3. Data Collection Channels

21.5. Data Cleaning 

21.5.1. Phases of Data Cleansing
21.5.2. Data Quality
21.5.3. Data Manipulation (with R)

21.6. Data Analysis, Interpretation and Evaluation of Results 

21.6.1. Statistical Measures
21.6.2. Relationship Indices
21.6.3. Data Mining

21.7. Viewing Data 

21.7.1. Suitable Display According to Data Type
21.7.2. End-User Considerations
21.7.3. Executive Models of Results Presentation

21.8. Data Warehouse (Datawarehouse) 

21.8.1. Elements that Comprise it
21.8.2. Design
21.8.3. Aspects to Consider

21.9. Data Availability  

21.9.1. Access
21.9.2. Uses
21.9.3. Security/safety

21.10. Practical Applications

21.10.1. Data Exploration
21.10.2. Manipulation and Adjustment of Patterns and Structures
21.10.3. Test Application and Modeling

Module 22. Data Protection 

22.1. Data Protection Regulations  

22.1.1. Regulatory Framework
22.1.2. Definitions
22.1.3. Subjects Obliged to Comply with the Regulations

22.1.3.1. Differences between Controllers, Joint Controllers and Processors

22.1.4. The Data Protection Officer

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

22.2.1.  Prohibited Practices
22.2.2. High-Risk Artificial Intelligence Systems
22.2.3. Innovation Support Measures

22.3. Principles Relating to the Processing of Personal Data 

22.3.1. Fairness, Loyalty and Transparency
22.3.2. Purpose Limitation
22.3.3. Data Minimisation, Accuracy and Limitation of Retention Period
22.3.4. Integrity and Confidentiality
22.3.5. Proactive Responsibility

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

22.4.1. Consent
22.4.2. Contractual Relationship or Pre-contractual Measures
22.4.3. Fulfillment of a Legal Obligation
22.4.4. Protection of Vital Interests of the Data Subject or Another Person
22.4.5. Public Interest or Exercise of Public Powers
22.4.6. Legitimate Interest: Weighing of interests

22.5. Individuals Rights

22.5.1. Transparency and Information
22.5.2. Access
22.5.3. Rectification and Deletion (Right to be Forgotten), Limitation and Portability
22.5.4. Opposition and Automated Individual Decisions
22.5.5. Limits to Rights

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

22.6.1. Identification of Risks and Threats to the Rights and Freedoms of Individuals
22.6.2. Risk Assessment
22.6.3. Risk Management Plan

22.7. Techniques for Ensuring Compliance with Data Protection Regulations

22.7.1. Identification of Proactive Accountability Measures
22.7.2. Organizational measures
22.7.3. Technical Measures
22.7.4. The Register of Processing Activities
22.7.5. Security Breach Management
22.7.6. Codes of Conduct and Certifications

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

22.8.1. EIPD Needs Assessment
22.8.2. Evaluation Methodology
22.8.3. Identification of Risks and Threats
22.8.4. Prior Consultation with the Supervisory Authority

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

22.9.1. Data Access or Data Processing Contract
22.9.2. Contracts between Co-Responsible Parties
22.9.3. Responsibilities of the Parties
22.9.4. Definition and Safeguards to be Adopted in International Transfers

22.10. Control Authorities. Violations and Penalties

22.10.1. Violations
22.10.2. Fines
22.10.3. Penalty Procedure
22.10.4. Control Authorities and Cooperation Mechanisms

Module 23. Business Intelligence and Artificial Intelligence Strategies and applications 

23.1. Financial Services

23.1.1. The Implications of Artificial Intelligence (AI) in Financial Services. Opportunities and Challenges
23.1.2. Use Cases
23.1.3. Potential Risks Related to the use of AI
23.1.4. Potential Future Developments/uses of AI

23.2. Implications of Artificial Intelligence in the Healthcare Service 

23.2.1.  Implications of AI in the Healthcare Sector. Opportunities and Challenges
23.2.2. Use Cases

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

23.3.1. Potential Risks Related to the use of AI
23.3.2. Potential Future Developments/uses of AI

23.4. Retail 

23.4.1. Implications of AI in the Retail. Opportunities and Challenges
23.4.2. Use Cases
23.4.3. Potential Risks Related to the use of AI
23.4.4. Potential Future Developments/uses of AI

23.5. Industry 4.0 

23.5.1. Implications of AI in the 4.0 Industry. Opportunities and Challenges
23.5.2. Use Cases

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

23.6.1. Use Cases
23.6.2. Potential Risks Related to the use of AI
23.6.3. Potential Future Developments/uses of AI

23.7. Public Administration

23.7.1. Implications of AI in Public Administration: Opportunities and Challenges
23.7.2. Use Cases
23.7.3. Potential Risks Related to the use of AI
23.7.4. Potential Future Developments/uses of AI

23.8. Educational 

23.8.1. Implications of AI in Educational: Opportunities and Challenges
23.8.2. Use Cases
23.8.3. Potential Risks Related to the use of AI
23.8.4. Potential Future Developments/uses of AI

23.9. Forestry and Agriculture 

23.9.1. Implications of AI in Forestry and Agriculture. Opportunities and Challenges 
23.9.2. Use Cases
23.9.3. Potential Risks Related to the use of AI
23.9.4. Potential Future Developments/uses of AI

23.10. Human Resources 

23.10.1. Implications of AI for Human Resources Opportunities and Challenges
23.10.2. Use Cases
23.10.3. Potential Risks Related to the use of AI
23.10.4. Potential Future Developments/uses of AI

Module 24. Optimization of the company's human capital

24.1. Human Capital in the Company

24.1.1. Value of Human Capital in the Technological World
24.1.2. Managerial Skills
24.1.3. Paradigm Shift in Management Models

24.2. Competencies of the Director 

24.2.1. Management Process
24.2.2. Management Functions
24.2.3. Group Leadership Management in Companies. Group Relations

24.3. Corporate Communication 

24.3.1. The Company's Communication Process  
24.3.2. Interpersonal Relations in the Company  
24.3.3. Communication Techniques for Change  

24.3.3.1. Storytelling  
24.3.3.2 Assertive Communication Techniques. Feedback, Consensus

24.4. Business Coaching 

24.4.1. Business Coaching
24.4.2. The Practice of Coaching
24.4.3. Types of Coaching and Coaching in Organizations

24.4.3.1. Coaching as a Leadership Style

24.5. Business Mentoring

24.5.1. Mentoring in the Company
24.5.2. The 4 processes of a Mentoring Program
24.5.3. Benefits of this Business Tool

24.6. Mediation and Conflict Resolution in the Company 

24.6.1. The Conflicts
24.6.2. Preventing, Addressing and Resolving Conflict
24.6.3. Stress and Work Motivation

24.7. Negotiation Techniques 

24.7.1. Negotiation at the Managerial Level in Technology Companies
24.7.2. Strategies and Main Types of Negotiation

24.7.2.1. The Figure of the Negotiating Subject  

24.8. Enterprise Change Management

24.8.1. Factors of Organizational Change
24.8.2. Strategic Planning
24.8.3. Organizational Change Management

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

24.9. Techniques for Improving Equipment Performance

24.9.1. Teamwork Techniques
24.9.2. Delegating in work Equipment

24.10. Focus Group. Classification 

24.10.1. The role of the Dynamizer
24.10.2. Group Dynamics Techniques

24.10.2.1. Brainstorming+
24.10.2.2. Philps 6/6
24.10.2.3. Hot Air Balloon D