ENAE INTERNATIONAL BUSINESS SCHOOL
CENTRO ADSCRITO A LA UNIVERSIDAD DE MURCIA Y A LA UNIVERSIDAD POLITÉCNICA DE CARTAGENA
Course in

BUSINESS ANALYTICS AND INTELLIGENCE SYSTEMS LAB

Area
Tecnología/Digital/Innovación/Data Science
Modality
Virtual Live
Duration
Start date

We are currently witnessing explosive growth in data generation, with more information estimated to be produced in an hour than in an entire year just a few decades ago. This phenomenon, known as the explosion of data, presents both a challenge and an opportunity for organisations.
 

Companies are faced with the imperative need to transform this sea of data into valuable and actionable information. In this context, Data Warehouses are emerging as essential technological foundations. These storage and processing infrastructures allow companies to consolidate data from various sources, facilitating comprehensive and strategic analysis.
 

The impact of Data Warehouse technology on companies is undeniable: it improves decision-making, optimises operational efficiency and provides a holistic view of business performance. In this course, we will not only explore the fundamentals of Data Warehouses, but also understand their relevance in today's business landscape.

Discover the key modules and concepts

BUSINESS INTELLIGENCE (BI)

  • What is Business Intelligence?
  • BI diagram.

DATA WAREHOUSE

  • What is a Data Warehouse?
  • Data Warehouse Architecture.
  • Fundamental components.

RELATIONAL DATABASES

  • Introduction and concepts.
  • OLTP and ACID.

ETL PROCESS

REPORTING AND DASHBOARDS

INTRODUCTION TO SQL

Área
Tecnología/Digital/Innovación/Data Science
Edition
Modality
Virtual Live
Start date
Start the
admission process

Description

In any company and sector, effective data management becomes essential to facilitate decision-making and stand out from the competition. For this reason, Business Intelligence becomes an essential tool, as it can be the key to properly directing or redirecting a business to the next level.
 

However, in order to work with good practices and correctly understand Business Intelligence, it is essential to acquire knowledge about what a Data Warehouse is and how to apply it in various ways in a business environment.

Throughout the course, the student will understand the concepts and models essential for its proper development, as well as its usefulness in the field of Business Intelligence.
 

In addition, there will be an in-depth look at Big Data, recognising the importance of broadening the horizon to understand the added value of artificial intelligence and advanced analytics.
 

In addition, two face-to-face workshops will be held: one focused on providing students with a fundamental knowledge of SQL and practice in its application, and another focused on working with the Microsoft cloud platform (Azure), where a proof of concept of a Data Warehouse in a cloud environment will be developed.

Objectives

  • Identify the fundamental concepts and the importance of a Data Warehouse as part of a Business Intelligence solution.
  • Structure and understand the different phases in an ETL scheme, as well as the solution to possible problems working with Big Data.
  • Manage and apply the language SQL.
  • Work with the Microsoft cloud for the development of data architectures.
  • Propose and develop ideas and solutions that provide added value in processes, products or services.

Methodology

ENAE uses an active and participative methodology, ‘learning by doing’, which alternates the presentation of concepts, techniques and analysis methods with the development of practical cases reflecting real business situations.
 

By promoting teamwork, the aim is to achieve the integration of all members and to resolve the cases presented more effectively, through the exchange of different points of view, opinions and experiences. Students will learn from the trainers but also from the professional experiences of their colleagues.

If you prefer, you can contact our advisor Arantxa García.
You can do this by calling +34 968456793
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