Master in Big Data and Data Intelligence

Study mode:On campus Study type:Evening Languages: Spanish
Local:$ 3.51 k Foreign:$ 3.51 k  
StudyQA ranking:2833 Duration:1 year

Photos of university / #insabarcelona

Intelligent data management becomes increasingly necessary especially now, as traditional concepts have evolved complex and diverse structures and therefore need higher quality sources and consistency.

  • Itakes: February and October
  • Duration: 1 año académico (Febrero a Febrero)
  • Modality: Presencial
  • Place: Barcelona
  • Language: Español
  • Price: 3.300 €
  • Schedule Tuesday and Thursday 19h to 21:30h

Objectives

  • Knowledge of data processing tools for both small and large companies and corporations.
  • Deepen knowledge to collect, aggregate, identify, give quality assurance and data persistence and even distribution.
  • To train professionals to intelligently manage the volume of data and generate strategic and innovative proposals.

Recipients

  • Graduates and professionals who wish to expand their business horizons.
  • Experienced professionals who want to take on new tasks and responsibilities.
  • Companies seeking staff expertise.
  • Graduates in Vocational Intermediate or Higher Grade seeking practical preparation to enter the workforce.

Professional outings

  • Data Management
  • Strategic Director

INSA offers the possibility of internships in companies during the period of delivery of the Master’s

Evaluation and Accrediation

The program evaluation system is composed of the attendance at meetings, half a partial evaluation of the course and the preparation and presentation of the final project.

After successful testing and evaluation of the program, as long as there is the minimum attendance required, students obtain the title of Master in Big Data & Data Intelligence of INSA Business, Marketing & Communication School.

Modules

Module 1
Descriptive Analysis Why do we want to analyze the data? What data do we need?
Module 2
Repository construction analysis. How to save the information.
Module 3
Definition and creation of variables. Where to start analyzing.
Module 4
Graphical representation variables. What and how to measure results.
Module 5
Defining indicators and validating results. Amount of data to analyze.
Module 6
Data Mining. Can we reduce the number of variables for analysis? Relations between events / hidden relationships. Grouping of users and / or products. Forecasts of behavior. Application of Analysis to the environment 2.0.
Module 7
Big Data. Strategic management of data flow. Generate economic value through the capture and analysis. Lifetime data. Improved Customer Service and competitive. Performance, segmentation and automation.
Module 8
Case Study. How to apply the acquired knowledge to a practical case.

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