TecnoCampus Foundation
eCampus
University Business
eCampus

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General information

Subject type: Optional

Coordinator: Joan Triadó Aymerich

Trimester: Third term

Credits: 6

Teaching staff: 

Miguel Fenollosa Pérez

Teaching languages

  • English

The subject will be taught in English.

Reference bibliography is available in English. Also some activities may be required to be done in English.

Skills

Specific skills

  • EC17: Applied knowledge of business organization.

Description

Optional subject framed in the block of the mention in Intelligent Manufacturing in Industry 4.0, an eminently practical approach to data processing aimed at supporting decision-making.

The subject delves into the use of analytical tools for its application in specific cases of the different areas of management of the industrial company, paying special attention to issues related to the Business intelligence and the presentation of results in the form of dashboards.

During the course we work with specific data analytics tools applied to specific cases on topics such as quality control or business intelligence, and using the ABP (Project-Based Learning) methodology in order to know some of the practical problems involved in using these tools when working with specific data sets.

Contents

Module 1: Introduction to Business & Market Intelligence

What we mean by Business Intelligence. The data used to manage the business and to design the marketing strategy. Automation of data acquisition and processing to support decision making.

Module 2: Identification of key indicators, Key Performance Indicators (KPIs)

Identification of the KPIs according to the business objectives and the mission of the area of ​​the company to be managed and determination of the associated data. Data acquisition for KPI maintenance. Elements necessary to obtain it (sensory). Restrictions, data quality and associated costs. Determination of the interest / cost ratio.

Module 3: Data Analysis and Monitoring and Process Control.

Application of data analytics techniques to process monitoring and control. Case study.

Module 4: Business Intelligence, Business intelligence.

Application of data analytics techniques to business intelligence. Case study.

Module 5: Dashboards, Dashboards.

Representation and interpretation of results. Type of Scorecard according to its purpose and scope. Dashboard Design Tools

Evaluation system

The evaluation of the subject will be based on the results obtained by the working group throughout the term. Part of the evaluation is common to all members of the group, depending on the results achieved in the projects; and another is individual based on the results of the functional area for which each student is responsible, and the results of the evaluation of Activity 3 (Exam).

The final grade will be calculated using a weighted average of the following weights:

- Activity 1: 30%

- Activity 2: 40%

- Activity 3: 30%

Any activity not delivered or delivered late will be considered scored with zero points. Failure to attend a session automatically excludes from the evaluation of the corresponding activity, being considered scored with zero points.

A minimum score of 35 out of 100 will be required in all activities in order to be assessed.

REFERENCES

Basic

Howson, Cindi (2013). Successful Business Intelligence: Unlock the Value of BI & Big Data, Second Edition. US: McGraw-Hill Osborne Media.

Sherman, Rick (2015). Business Intelligence Guidebook: From Data Integration to Analytics (1st ed.). Morgan Kaufmann Publishers Inc., San Francisco, CA, USA. DOI: https://doi.org/10.1016/C2012-0-06937-2.

Loshin, David (2013). Business Intelligence: The Savvy Manager's Guide (2nd ed.). Morgan Kaufmann Publishers Inc., San Francisco, CA, USA. DOI: https://doi.org/10.1016/C2010-0-67240-3.

Complementary

Larson, Brian, Corley, Dan (2020). Data analysis with Microsoft Power BI, First Edition. US: McGraw-Hill Osborne Media.