110802 - APPLIED DATA ANALYSIS

Subject type: Optional

Coordinator: Julián Horrillo Tello

Trimester: Third term

Credits: 6

The subject will be taught in Catalan and / or English.

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

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.

At the end of the course, students will have achieved the following learning outcomes:

- Solvently apply data analysis techniques focused on their application in specific cases related to different areas of management of the industrial company.

- Clearly define the most relevant Key Performance Indicators (KPIs) in accordance with industrial / business processes and activities; as well as the methodologies for calculating them, input data, and other necessary parameters.

- Design Dashboards for a clear and concise visualization and interpretation of data and KPIs.

The subject will combine master sessions of explanation of the main concepts of the subject and debate on the same; and practical sessions focused on the development of the Business Intelligence Project (Learning Activities 1 and 2).

For each activity, teachers will report on the particular rules and conditions that govern them. This information will be communicated in the physical classroom and / or published in the virtual classroom.

One-on-one activities presuppose the student's commitment to carry them out individually. All activities in which the student does not fulfill this commitment regardless of their role (origin or destination) will be considered suspended.

Likewise, the activities to be carried out in groups presuppose the commitment on the part of the students who make it up to carry them out within the group. All activities in which the group has not respected this commitment regardless of its role (origin or destination) will be considered suspended. The responsibility for the results of the work lies with the group, and not with the individuals who make it up. In any case, teachers can, based on the information they have, customize the grade for each member of the group.

We will work with Python / RStudio for Data Processing and Analysis, and with the Microsoft Office Suite for Data Visualization and Dashboarding.

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

The subject is presented with an eminently practical component, focused on the elaboration of a project - separated into two works for its sequencing and compartmentalization of the tasks to be evaluated - and a written exam or test that will include theoretical concepts. and practical.

Activity 1: Business Intelligence Project: Data analytics project applied to a specific case.

The first part of the project includes an analysis of the process, its quality objectives and KPI indicators that assess the efficiency of the process and support the decision-making process.

Approach and justification of the data acquisition and processing project.

The work will be done in groups of up to 5 students.

Activity 2: Business Intelligence Project: Data processing and presentation of results.

Carrying out the data processing project to determine the quality and efficiency of the process.

The proposed analyzes must be oriented towards decision-making for the improvement of the process.

Special attention is paid to the design of a Dashboard, with a user interface that facilitates the identification of problems and decision-making for their solution.

The work will be done in groups of up to 5 students.

Activity 3: Exam

Written test to evaluate the theoretical and practical concepts developed throughout the course, especially the main aspects related to the work done throughout the course

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.

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.

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