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"

The objectives of this professional master’s degree have been established based on realistic and necessary goals for professionals in the sector. Students will be able to progressively verify their learning and progress in the mastery of the contents so that, at the end of the course, they will have achieved professional growth.

Realistic, achievable and high-impact goals for your professional training"

General Objectives

• Offer students immersion in the new social and technological context in which Visual Analytics tools are framed. This high-complexity content and uncertainty is increasingly supported by decision making based on data analysis and visualization
• Obtain and enhance fact-based critical thinking for strategic decision making 
• Understand the value of the changing environment and facilitate students’ connection to entrepreneurship and new knowmad ways of working
• Analyze the data produced and draw conclusions using statistical tools to make the most appropriate decisions at all times 
• Learn the introductory concepts of statistics; statistical reasoning; representing relationships between different variables, among others
• Acquire in-depth knowledge of the principles of probability that are the basis for inferential statistics, which will allow us to contrast conjectures (hypothesis testing) about what a given population is like
• Understand information sources and the value they bring to the creation of new innovative business models
• Know and use statistical tools to solve problems in the Big Data field
• Know how the combination of all the data flowing through the Internet can be combined in order to define new strategies applicable to different industrial, business, financial sectors, etc., within different fields, such as energy, health, economy or communication
• Learn the different techniques for data analysis and exploitation and visualization and interaction techniques, all closely linked to the role of Data Scientists and their contribution to the anticipation and vision for the execution of innovation processes that allow for efficient changes in organizations
• Assimilate concepts, techniques, methodologies and knowledge of languages that will be useful to apply in big data mining
• Further study Artificial Intelligence algorithms and techniques such as decision trees, classification and association rules, neural networks or Deep Learning
• Apply Data Mining tools to solve learning problems, interpreting the results obtained, as well as the ability to design an intelligent system capable of inferring new knowledge
• Understand databases, from traditional to unstructured, where data requiring other types of processing, such as audio or video streams, will be stored
• Learn about the importance of having cloud computing for processing large volumes of data and how all this Big Data can be ingested into tools that allow us to obtain and infer patterns in seemingly unrelated data
• Delve into the Hadoop framework and its file system HDFS (Hadoop Distributed File System), which provides tools and techniques for distributed storage and processing of large amounts of data
• Know how to apply tools for parallel processing: MapReduce, devised by Google in 2004, or Spark, now under the auspice of the Apache Software Foundation
• Understand how high-performance, low-latency platforms work for real-time manipulation of data sources that need to respond to service demands operating in the millisecond range
• Offer students a 360-degree view of management, providing them with a balance between technical and managerial preparation
• Enhance management and leadership skills to successfully manage teams and projects
• The student will become a resilient leader through the management of emotions, conflict and crisis, fundamental skills in the current context and others oriented to decision making, negotiation and change management
• Acquire the skills for strategic project management through the contribution of best practices collected under the PMI, methodologies such as Kimball or a unique methodology in the world:
• SQuID, developed by a leading Spanish company in Big Data
• Understand the legal aspects related to user privacy and their right to protect their data, aspects to be complied with by any system that makes effective use of third-party data
• Understand the need for security in data storage, management and access along with the pillars of information security: integrity, confidentiality, availability and traceability
• Study, in-depth, the ethics of data and its possible uses in today's societies
• Acquire basic knowledge to obtain a vision on the relevance of Marketing in the strategy of any company and how the effective management of data analysis techniques contributes to the definition of more accurate strategies reaching the market
• Learn to accurately define the consumer by learning specific skills and finding and analyzing the necessary information
• Obtain information based on data from web searches, in order to define a strategy based on realities, i.e. existing data
• Know how to differentiate the offer, thus providing the ability to think in the same way as the consumer, detecting the attributes they want
• Expand knowledge on the use of open sources to combine with other existing data within the organization
• Learn about a case study of application in the world of Big Data to Marketing with MasterLead, which provides a tool to assess the probability of a lead becoming a customer
• Learn the graphical representation of data by means of statistics, maps, diagrams or schemes with the objective of making data visible to a given audience, but above all to bring out the relevant information hidden in the selected data set
• Be able to practice storytelling with data to understand how to represent data and its visual representations
• Understand Keim's visual analytics process, which shows how to apply Visual Analytics techniques to the business world 
• Understand different types of reports: strategic, operational and management, as well as the types of charts and their function
• Learn how to use IBM's Many Eyes tool that allows you to create different types of data visualizations such as infographics, maps, word count visualization, bar charts, etc.
• Obtain capabilities in three popular libraries such as Google Charts, JQuery plug-ins for visualizations and Data-Driven Organizations, also known as D3, one of the most powerful libraries currently on the market
• Gain in-depth knowledge of another set of tools that are widely used in various industries such as Matlab, Tableau, SAS Visual Analytics or Microsoft Power BI, where you can explain the history of a dataset through visualizations

Specific Objectives

Module 1. Visual Analytics in the Social and Technological Context

• Understand the new social, economic and business dynamics of the world
• Understand the value of new environments as an opportunity for entrepreneurship
• Develop analytical skills in changing environments
• Identify and focus on new scenarios and their opportunities 
• Develop analytical and critical thinking for strategic decision making
• Understand new profiles in the current context in order to define strategies adapted to them
• Generate differential value in our ability to make decisions 
• Understand the new business environment in order to address transformation processes in organizations

Module 2. Data Analysis and Interpretation

• Know the different theories for data analysis and interpretation 
• Identify the most common descriptors for a dataset 
• Understand and evaluate the applicability of different descriptors to an existing dataset 
• Know how to carry out hypothesis testing and its applicability to the world of data analysis
• Learn how to interpret the different existing regression techniques 

Module 3. Data Analysis Techniques and AI

• Understand the different techniques for data analysis 
• Design joint strategies of statistical and artificial intelligence techniques for the development of descriptive and predictive systems applied to the reality of a dataset 
• Understand the operation and characteristics of common mass data processing techniques
• Identify techniques oriented to statistical analysis, artificial intelligence and mass data processing

Module 4. Data Analysis Tools

• Understand the environments most used by Data Scientists 
• Know how to process data in different formats from different sources
• Learn from the need to guarantee the veracity of the data as a prior step to its processing 
• Identify new technologies as pedagogical tools in the communication of the different business realities
• Know the latest trends in the creation of intelligent entities based on Deep learning and neural networks

Module 5. Database Management and Data Parallelization Systems

• Know the artificial intelligence techniques applicable for massively parallelized data processing on a given data set and according to previously defined requirements
• Know how to manage large volumes of data in a distributed manner
• Understand the operation and characteristics of common mass data processing techniques
• Identify commercial and open software tools oriented to statistical analysis, artificial intelligence and mass data processing

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

• Know and develop the Drive profile applied to mass data environments 
• Understand what and why advanced management skills generate differential value in data scientists 
• Develop strategic communication and presentation techniques 
• Understand the role of emotional intelligence in the context of Visual Analytics 
• Identify key concepts in Agile team management
• Develop and leverage digital talent in data-driven organizations 
• Develop emotional management skills as a key to performance-focused organizations 

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

• Know the best practices in PMI applied to the world of Big Data
• Learn Kimbal methodology 
• Know the SQuID methodology and its applicability in the development of projects with large volumes of data
• Identify the legal issues of application related to the capture, storage and use of user data 
• Know how privacy can be provided in Big Data 
• Anticipate ethical risks and benefits derived from the application of big data techniques that may occur in real situations

Module 8. Client Analysis. Applying Data Intelligence to Marketing

• Know the different types of marketing and how they are applied in organizations and their influence on business strategies
• Be able to design a central intelligence system (CRM) for decision support based on data analysis and visualization, and focused on the company's own context
• Provide an introduction to the Internet as a massive source of real data based on user searches that can be utilized for decision making
• Analyze the technologies underlying the various web systems 
• Develop open source intelligence solutions, exploiting available data sources
• Learn about application of data to improve marketing and sales in business organizations 

Module 9. Interactive Visualization of Data

• Understand how patterns found in a data set can be made visible in order to generate a common interpretation of the underlying reality 
• Understand the scalability of individual representations 
• Understand the difference between Visual Analytics and information visualization
• Understand the process of Keim's visual analysis 
• Evaluate the different data visualization methods applicable depending on the information to be conveyed

Module 10. Visualization Tools

• Know how to generate diagrams that visually represent the chosen situation from a set of data
• Be able to combine the different techniques studied for the design of original visualizations
• Understand how, starting from a design and a set of previous data, a visualization implementation that meets the defined requirements can be carried out
• Identify the usability and interactivity needs of data visualization methods and be able to develop a new version of the visualization that improves these aspects
• Design a system that combines data capture and storage techniques, as well as data analysis and visualization, to represent existing patterns in that data set

A stimulating journey of professional growth designed to keep you interested and motivated throughout the entire program"