The Master in Information Systems, mention in business intelligence and big data analytics (Big Data) aims to develop and combine competencies of the applicability of technologies, in the area of engineering and technology of an organization using the software tools that are They apply in professional environments to obtain training in the area of Business Analytics and Big Data, specifically in the application of database management, programming for information management, business administration models, among others, for effective exercise and efficient of these functions that allow managing the organization's data and digital information.
This program seeks that the professionals graduated from the Master in Information Systems, mention in business intelligence and big data analytics (Big Data), acquire the following professional and personal characteristics as part of their professional profile:
- Accredit theoretical and practical experience in the area of Big Data and Business Analytics.
- Be trained to perform the functions of Chief Data Officer (CDO), big data architect and data engineer.
- Lead analysis processes of organizations' business intelligence and data science framework.
- Advise the information technology management units in the development of digital information and data management systems.
- Be a consultant in the development of projects that link the management of databases and business intelligence.
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Overcoming this mastery you will get
- Master in Information Systems, mention in business intelligence and big data analytics from the International University of Ecuador UIDE (Postgraduate course registered at CES and recognized by SENESCYT, valid in Ecuador, Colombia, Peru and Bolivia ).
- Own master's degree in Big Data and Business Analytics certified by the Nebrija University of Spain .
- Professional Master in Big Data and Business Analytics by IMF Academic Institution of Spain .
* Title issuance fees not included.
Multiple skills that will open doors for you.
The understanding of technical use complements the business vision, so that graduates will be able to reason in depth about the applicability of technologies, as well as apply analytical tools and techniques in specific situations.
Know the concepts of the different disciplines focused on database management, programming for information management and business administration models in order to have an overview of the storage and management of data and information and their implementation strategies in the business.
- The professional will be trained in social development processes through social responsibility for the enrichment of cultures and knowledge.
- The professional will be able to work within the framework of business intelligence and data science of organizations.
- The professional will be able to carry out a competent job as Chief Data Officer (CDO), big data architect and data engineer
- The professional will be able to establish new ways to apply their knowledge in big data and business analytics.
Class Schedule: The synchronous online class schedule will be: Saturday 08:00 - 17:00 and Sunday 08:00 - 17:00.
The design of the Master in Big Data and Online Business Analytics program is designed to cover 4 nuclei and 10 subjects.
- Nuclei: Database management, Information management programming, Business administration models and Scientific Research Methodology.
The curriculum structure is designed to gradually develop and achieve competencies over 2 periods.
The master has 10 professors, authors and tutors of all subjects to guarantee direct contact with students, teachers and the University. All teachers validate 120 hours of training in specific training in online education.
Likewise, there is an IT expert who will be responsible for providing support and technical support to users of the platform and learning resources, as well as connectivity and access to information and communication technologies.
Be an active participant in your learning process. Having sufficient skills and knowledge in the management of communication, computer or telecommunications technologies, systems engineering, software or programming.
Have a high discipline in managing and scheduling your study time.
Have a self-critical capacity to carry out self-evaluations in a way that allows them to achieve the proposed learning results.
Be disciplined to meet the schedule of the established program. Be willing to maintain continuous communication with the tutor, and actively interact with peers to promote collaborative learning.
The third level graduates who can preferably access the program according to the nomenclature of professional titles and academic degrees according to the level of training are:
- Broad field: Information and communication technologies (TICS)
- Copy of the third level certificate registered in the SENESCYT and in the case of foreign titles these must be apostilled or legalized by consular route.
- Registration Form (online).
- Copy of personal documents: ID, voting slip, passport-size photo.
- Curriculum vitae.
- Preferably one year of proven professional experience (labor certificates).
- A personal letter of recommendation.
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Contents of the program
- Using virtual machines and command shell
- Fundamentals of programming in Python
- Relational Database Fundamentals
- Fundamentals of Internet Technologies
- Share data, code and resources in repositories
- Fundamentals of data processing with the Python scientific stack
Models and learning
- R language and data processing
- Exploratory data analysis
- Probability and Statistical Inference
- Linear models and statistical learning
- Logistic regression, restricted ridge and lasso models and descending gradient
- GLMS and time series
- Introduction to machine learning
- Supervised models
- Unsupervised models
- Features engineering and model selection
- Connectionist models
- Association rules and market basket analysis
Natural Language Processing (PLN)
- Historical and technological introduction
- Pln tools I: NLTK
- PLN II Tools: Brat and Gate
- Text mining I: clustering
- Text mining II: feeling and themes
- Other PLN applications and techniques
- Introduction to business intelligence
- Data warehouses and analytical databases
- Extraction, transformation and loading tools
- Business intelligence applications
- Data visualization fundamentals
- Visualization tools
Big data infrastructure
- Data processing with Hadoop
- Hadoop tools
- Data processing with Spark
- Streaming architectures
- Streaming architecture components
- Platforms and Apis in the cloud
Data storage and integration
- Unconventional databases
- Document-based database models
- Column-based database models
- Graph-based database models
- Key-value based database models
- Data acquisition
Big Data Analytics
- The Big Data business case
- Big Data projects
- Analytical applications by sector
- Emerging technologies in analytics
- Team management and agile methods
- Regulatory aspects of data processing
- Scalable analytics case study
- Analytics case study on social networks
- Internet Of Things case study
- Case study in financial analytics (the rating of companies)
- Customer analytics case study: Location Analytics
- Information retrieval techniques case study
Degree plan and integrated management systems
- Integrated management and social responsibility systems
- Design and implementation of projects with applied research and / or development components
- Design and writing of high-level professional articles
- Analysis of practical models for the development of the exam of complex character
About the School
OpenUIDE nace con el objetivo de ser la Universidad a distancia de referencia en el Área Andina. Respaldada y avalada por la Universidad Internacional del Ecuador, una universidad joven, innovadora, p ... Read More