Be trained by the best teachers with most innovative educational system and the security and solvency of the largest online university right now

master visual analytics big data

Apply the latest techniques in Visual Analytics to data work by harnessing the enormous capacity that arises from the combination of human knowledge and the storage power of computers"

Throughout the years, Big Data has become something indispensable in our lives Most people use electronic devices or technology constantly collects data This information is of great value for companies which will allow them to use those reports to improve, for example, the process for creating new products or solving possible company weakness 

Currently, the collection and storage process for trillions of pieces of data which is produced every day has improved considerably However, for a human being it is still impossible to analyze all that information and, therefore, tools or automated methods are needed to make the job easier  

The use of Visual Analytics techniques makes it possible to improve the decision-making process by combining human knowledge with the enormous capacity that computers have for data processing and storage, with the goal being to find solutions to complex problems 

To meet the growing need for professionals who are specialized in Visual Analytics and Big Data, this prestigious program was created, which provides a strategic vision to participants for how to apply new data analysis technology in the world of business, with the goal of developing innovative services based on the information analyzed  

Throughout these months of training, the students will get a complete overview of the latest developments in data analytics that will take them through the most intensive educational journey, to prepare them to be the star profile at this time, delving into booming areas of study such as:

  • Data and AI Analysis Techniques
  • Capture and Information Storage
  • Artificial lntelligence technique   
  • Engineering for Massive Parallel Data Processing   
  • Visualization Techniques and Tools

A unique opportunity to specialize and stand out in a booming sector with a high demand for professionals 

Contarás con materiales y recursos didácticos innovadores que facilitarán el proceso de aprendizaje y la retención por más tiempo de los contenidos aprendidos”

This Professional Master’s Degree in Visual Analytics and Big Data contains the most complete and up-to-date program on the market The most important features of the training include: 

  • Practical case studies presented by experts 
  • The graphic, schematic, and practical contents with which they are created, provide scientific and practical information on the disciplines that are essential 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

You will have innovative teaching materials and resources that will facilitate the learning process and the retention of the contents learned for a longer period of time"

The program’s teaching staff includes professionals from 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 training programmed to train 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 academic year For this purpose, the professional will be assisted by an innovative interactive video system created by renowned and experienced experts.  

A very complete training, created with a strong focus on quality and bringing our students to the highest level of skill"

maestria visual analytics big data

A complete update that will provide you with the working capacity of a specialist in the field"


The syllabus of the Professional Master’s Degree is structured as a comprehensive tour through each and every one of the concepts required to understand and work in this field With an approach focused on practical application that will help you grow as a professional from the very first moment of training

mejor maestria online visual analytics big data

A comprehensive syllabus focused on acquiring knowledge and converting it into real skills, created to propel you to excellence"

Module 1. Visual Analytics in the Social and Technological Context

1.1. Technological Waves in Different Societies Towards a  ‘Data Society’
1.2. Globalization. Geopolitical and Social World Context
1.3. VUCA Environment Always Living in the Past
1.4. Knowing New Technologies: 5G and IoT
1.5. Knowing New Technologies: Cloud and Edge Computing
1.6. Critical Thinking in Visual Analytics
1.7. Know-mads Nomads Among Data
1.8. Learning to Be an Entrepreneur in Visual Analytics
1.9. Anticipation Theories Applied to Visual Analytics
1.10. The New Business Environment. Digital Transformation

Module 2. Data Analysis and Interpretation

2.1. Introduction to Statistics
2.2. Measures Applicable to the Processing of Information
2.3. Statistical Correlation
2.4. Theory of Conditional Probability
2.5. Random Variable and Probability Distribution
2.6. Bayesian Inference
2.7. Sample Theory
2.8. Confidence Intervals
2.9. Hypothesis Testing
2.10. Regression Analysis

Module 3. Data Analysis Techniques

3.1. Predictive Analytics 
3.2. Evaluation Techniques and Model Selection 
3.3. Lineal Optimization Techniques 
3.4. Monte Carlo Simulations 
3.5. Scenario Analysis 
3.6. Machine Learning Techniques 
3.7. Web Analytics 
3.8. Text Mining Techniques 
3.9. Methods of Natural Language Processing (NLP) 
3.10. Social Network Analytics 

Module 4. Data Analysis Tools

4.1. Data Science R Environment
4.2. Data Science Python Environment
4.3. Static and Statistical Graphs
4.4. Data Processing in Different Formats and Different Sources
4.5. Data Cleaning and Preparation
4.6. Exploratory Studies
4.7. Decision Trees
4.8. Classification and Association Rules
4.9. Neural Networks
4.10. Deep Learning

Module 5. Database Management and Data Parallelization Systems

5.1. Conventional Databases
5.2. Non-Conventional Databases
5.3. Cloud Computing: Data Distribution Management 
5.4. Tools for the Ingestion of Large Volumes of Data
5.5. Types of Parallels
5.6. Data Processing in Streaming and Real Time
5.7. Parallel Processing: Hadoop
5.8. Parallel Processing: Spark
5.9. Apache Kafka

5.9.1. Introduction to Apache Kafka
5.9.2. Architecture
5.9.3. Data Structure
5.9.4. APIs Kafka
5.9.5. Case Uses

5.10. Cloudera Impala

Module 6. Data-Driven Soft Skills in Strategic Management in Visual Analytics

6.1. Drive Profile for Data-Driven Organizations
6.2. Advanced Management Skills in Data-Driven Organizations
6.3. Using Data to Improve Strategic Communication Performance
6.4. Emotional Intelligence Applied to Management in Visual Analytics
6.5. Effective Presentations
6.6. Improving Performance Through Motivational Management
6.7. Leadership in Data-Driven Organizations
6.8. Digital Talent in Data-Driven Organizations
6.9. Data-driven Agile Organization I
6.10. Data-driven Agile Organization II

Module 7. Strategic Management of Visual Analytics and Big Data Projects

7.1. Intriduction to Strategic Project Management
7.2. Best practices  in the Description of Big Data Processes
7.3. Kimball Methodology
7.4. SQuID Methodology
7.5. Introduction to SQuID Methodology to Approach Big Data Projects

7.5.1. Phase I. Sources
7.5.2. Phase II. Data Quality
7.5.3. Phase III. Impossible Questions
7.5.4. Phase IV. Discovering
7.5.5. Best Practices in the Application of SQuID in Big Data Projects

7.6. Legal Aspects in the World of Data
7.7. Big Data Privacy
7.8. Cyber Security in Big Data
7.9. Identification and De-identification with Large Volumes of Data
7.10. Data Ethics I
7.11. Data Ethics II

Module 8. Client Analysis. Applying Data Intelligence to Marketing

8.1. Concepts of Marketing. Strategic Marketing
8.2. Relationship Marketing 
8.3. CRM as an Organizational Hub for Customer Analysis
8.4. Web Technologies
8.5. Web Data Sources
8.6. Acquisition of Web Data
8.7. Tools for the Extraction of Data from the Web
8.8. Semantic Web
8.9. OSINT: Open Source Intelligence
8.10. Master Lead or How to Improve Sales Conversion Using Big Data

Module 9. Interactive Visualization of Data

9.1. Introduction to the Art of Making Data Visible
9.2. How to do Storytelling with Data 
9.3. Data Representation
9.4. Scalability of Visual Representations
9.5. Visual Analytics vs. Information Visualization. Understanding That Its Not The Same
9.6. Visual Analysis Process (Keim)
9.7. Strategic, Operative and Managerial Reports
9.8. Types of Graphs and Their Application.
9.9. Interpretation of Reports and Graphs. Playing the Role of the Receiver
9.10. Evaluation of Visual Analytics Systems 

Module 10. Visualization Tools

10.1. Introduction to Data Visualization Tools
10.2. Many Eyes
10.3. Google Charts
10.4. jQuery
10.5. Data-Driven Documents I
10.6. Data-Driven Documents II
10.7. Matlab
10.8. Tableau
10.9. SAS Visual Analytics
10.10. Microsoft Power BI

estudiar online visual analytics big data