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The management of large volumes of data, its organization and the development of strategies in this regard are matters of great complexity. There is a whole theory on the subject, and you also have to take into account the legislation on data protection. Because this type of work is in high demand, there is a great demand for specialization in Big data.
Basic information of the Master Big Data Analytics
The Master Big Data Analytics of CEUPE is a Graduate Professional Degree. This lasts for a period of 12 months and is taught online, which encourages the student to harmonize their training with their family and professional life.
CEUPE presents payment facilities through monthly installments without any interest rate. In addition, applicants may apply for a scholarship.
CEUPE is endorsed and awarded in the main ranks by the most important international academic institutions. Among its awards, it has the Cum Laude Seal of Emagister, a leading entity in online training. Likewise, the Spanish Association of Business Schools has awarded the excellence of the CEUPE teaching staff and the quality of their master's degrees.
Competences to acquire with this master's degree
The team of professors has established four central objectives of the Master in Big Data so that the student, when they graduate, can master effectively:
1. Acquire a deep knowledge of Big data architecture and all the necessary tools to process and use the data.
2. Take advantage of the Big data application to achieve the best results with Big data analytics and advanced data analysis.
3. Learn to use all the tools that are required for a Data Science.
4. Obtain the essential knowledge to use, analyze and exploit the data.
Functions to be performed by the Big Data analyst
The professional skills of Big Data specialists include:
• Browse the areas for which data analysis is performed.
• Know the techniques of statistical analysis and their application.
• Know how to use algorithms to build mathematical models in their work.
• Ease of extracting and transforming data from structured and unstructured sources.
• Have the ability to program in Python language and work with the Bash command line.
• Know the frameworks and be able to apply them.
• Ability to work with data gaps.
• Employ digital security techniques.
• Manage data.
• Apply the typical scenarios of digital transformation.
• Use Big Data technologies in various areas (use cases).
Additionally, a Big Data analyst needs teamwork skills to help them interact with colleagues from related fields.
Who is this magister for?
The master's degree is aimed at people who want to develop or enhance the technical and analytical skills necessary for a successful career in business intelligence or big data.
It is also aimed at professionals in areas such as technology, business, quantitative or analytics who need to know business analytics methods and techniques to make better business decisions, have a much more comprehensive view of the organization or create innovation in large companies.
Also, for those people who, with some analytical skills, want to strengthen their technical skills to make a career in the big data industry.
Syllabus of the Master Big Data Analytics
The Big Data Analytics Master is structured in 7 modules, where the following topics are studied in depth:
• Analytical Tools and Notions of Big Data
• Big Data Infrastructure
• Programming Languages of a Data Science
• Tools - Libraries
• Data Study and Modeling
• Design of a Scalable Model
• Use cases
The Master in Big Data Analytics or Advanced Data Analytics is designed and structured by professionals in the field with extensive experience in the sector. The curriculum is organized as follows:
Analytical tools and basic concepts of big data : in this stage an overview of the concepts of big data architecture and advanced data analytics will be given. The concept of distributed computing and the benefits it offers will be explained and the main tools used for the processing and analysis of large amounts of data will be presented.
Big data infrastructure and advanced data analytics : in this phase we will delve into the architecture of the big data environment, knowing each of the main tools that will help us to start a project with the best possible guarantees of success, both at the processing and analytics.
Data analysis and modeling : this step explains how to analyze the available data and its nature from a morphological point of view, in order to carry out a modeling that allows to make the most of it.
Scalable Model Design : You will focus on understanding current models and, by understanding the data that can feed them, explore how to create a new scalable model aimed at obtaining and improving current results. The difference between local and distributed work will also be explained.
Professional opportunities of the Master Big Data Analytics
Big Data Analytics has many career opportunities that are currently among the most demanded professional profiles by multinational companies. A master's degree in which technical profiles such as computer scientists, programmers or engineers are those that are of interest in this postgraduate academic profile.