Professional master’s degree Visual Analytics and Big Data

This Program in Visual Analytics and Big Data will enable you to enter the world of Big Data as a professional capable of handling rational analysis, supported by a visual and interactive interface. A process that will allow you to acquire the knowledge you need to participate in the capture and storage of information, the analysis of data mining or the visualization of information. A program that will allow you to learn the most relevant innovations in automatic and visual data analysis with the exceptional quality of TECH, the largest university in the online teaching market.

University certificate

duration

12 months

Modality

Online

Schedule

At your own pace

Exams

Online

start date

Credits

60 ECTS

financing up to

12 months

Price

See price

The world's largest faculty of information technology”

Why study at TECH?

Get qualified with the best teachers, the most innovative educational system and the security and solvency of TECH Global University"

Over the years, Big Data has become indispensable in our lives. The majority of the population uses electronic devices or other technologies that are constantly collecting data. This information is of great value to companies as it allows them to use these reports to improve, the process of creating new products or address potential business deficiencies.

Nowadays, the collection and storage of the trillions of data produced every day has improved considerably. However, there are significant limitations in human beings' capacity to analyze this information and, therefore, tools or automatic methods are required to facilitate this task.

The use of Visual Analytics techniques makes it possible to improve decision making by combining human knowledge with the enormous data processing and storage capacity of computers, in order to find solutions to complex problems.

In response to the growing need for professionals specialized in Visual Analytics and Big Data, this prestigious program was created to provide participants with a strategic vision of the application of new data analysis technologies to the business world, for the development of innovative services based on analyzed information.

Throughout these months of the course, students will get a complete overview of the latest developments in data analytics that will take them through the most intensive educational path and prepare them in current star profiles delving into booming areas of study such as:

Data Analysis Techniques
Data Capture and Storage
Artificial Intelligence Techniques
Engineering for Mass Parallel Data Processing
Visualization Techniques and Tools

A unique opportunity to specialize in a growing sector and stand out as a successful professional.

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"

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 educational materials and resources that will facilitate the learning process and the retention of the content learned for a longer period of time”

Its teaching staff includes professionals from the sector who bring their work experience to this program, in addition to recognized specialists from leading societies and 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 academic course. For this purpose, the professional will be assisted by an innovative interactive video system created by renowned and experienced experts.

A highly comprehensive program, created with the objective of delivering the highest quality education, raising our students to the highest level of proficiency"

A full refresher course that will provide you with the working skills of a data analysis specialist"

Syllabus

The syllabus of this Professional master’s degree is structured as a complete 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.

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. The 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 and AI

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 Media 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: distributed data 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. Kafka APIs
5.9.5. Use Cases

5.10. Cloudera Impala

Module 6. Data-Driven Soft Skills in Strategic Management of 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. Introduction to Strategic Project Management
7.2. Best Practices in the Description of Big Data Processes (PMI)
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 Internet
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 Perform Storytelling with Data
9.3. Data Representation
9.4. Scalability of Visual Representations
9.5. Visual Analytics vs. Information Visualization. Understanding That It’s Not The Same Thing
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

A unique, key and decisive training experience to boost your professional development"

Professional Master's Degree in Visual Analytics and Big Data

Considering that the volume of data is growing rapidly, due to the improvement of data collection and storage systems, at TECH Global University we have created this program focused on the analysis of this type of information. From the approach of digital transformations in the geopolitical-social context of globalization, the curriculum deploys content relating to database management systems and parallelization, the strategic direction of projects in this area and the application of methods to marketing. On another level, observation, comparison and interpretation techniques (model evaluation and selection, linear optimization, scenario analysis, Machine Learning, Text Mining, NLP) and their respective tools (R and Python Data Science environment, static/statistical graphs, decision trees, classification and association rules, neural networks and Deep Learning) are covered. Consequently, thematic axes dedicated to the interactive visualization of information are presented. At the end of this complete course, our students will develop the necessary skills to perform integrally in this area.

Postgraduate course in Visual Analytics and Big Data

This TECH postgraduate course is an interesting opportunity to specialize in the application of strategic visions that favor the understanding of the information collected by organizations. With the knowledge gained during the year it takes to complete it, professionals will be empowered to design systems that simultaneously capture, collect, analyze and visually represent the data in order to prepare explanatory reports, where the existing patterns in the selected set are exposed. By mastering the criteria of usability and interactivity, you will become an expert in Big Data that will allow the sectors for which you work to know the service opportunities in order to expand their range of action. In addition, thanks to the situational methodology and problem-based learning, he/she will be prepared to face the challenges imposed by digital changes, offering services that facilitate the search for solutions to complex problems. In this way, the graduate of the Professional Master's Degree in Visual Analytics will be characterized by being a competent computer scientist, seasoned in anticipating the risks and benefits brought by the handling of large volumes of data.