DATA SCIENCE AND TECHNOLOGY INTELLIGENCE

Single discipline educational activity

Course Sheet

Course code:

DASTI19

Academic Year of enrolment:

2019

Year of supply:

2019/2020

Type of Course:

Elective Course

Degree:

Course of 2nd Cycle Degree in DIGITAL MARKETING

Disciplinary Sector:

Data Processing Systems

Location:

PESCARA

Credits:

Programme Year:

Professor and Collaborators:

TETI Antonio

Cycle:

Third four months

Hours of classroom activity:

Individual study hours:

114

Prerequisites:

Although no prerequisites are required, knowledge of the basic concepts of basic computer science is recommended.

Objectives

Educational objectives:
The teaching pursues the aim of preparing the student for the new challenges of the digital society. The course of study is aimed at creating the most requested figures in the context of the digitization of society and industry 4.0, in addition to other areas such as research, development and design centers, both in the public and private sectors. The course provides students with a solid basic methodological preparation in three areas: data mining, data analytics, machine learning, deep learning and computer science with particular attention to the use of algorithms. Furthermore, the teaching pursues the aim of providing students with advanced skills in the field of techniques and methodologies for the optimization of digital technologies in the corporate environment. The key skills that the most successful leaders should possess to ensure and enhance the value of the corporate business or government institutions include:
• foresight, understood as the ability to intercept the predisposition to run into threats or advantages for the organization;
• visionary capacity, understood as the ability to conceptualize an ideal future, based on forecasts that can be shared at an organizational level;
• system thinking, understood as the ability to perceive, synthesize and integrate all those elements (thoughts, ideas, opinions) that can allow to achieve a common purpose;
• motivation, or the ability to motivate different individuals to lead them to the most complete group collaboration. The ability lies in understanding what drives people to do certain things and using all the tools available to guide them in the same direction (personality intelligence);
• partnership, or the ability to develop strategic alliances with individuals, groups and organizations.
With this in mind, the thematic areas treated, according to the implementation of verticalized information technologies based on the different types, are:
• Technology Management
• Technology Scouting
• Strategic Management
• Innovation Management
• Knowledge Management
• Market Intelligence

Contents

Data Science is a sector that deals with the study of the set of methodological principles and multidisciplinary techniques aimed at the interpretation and construction of a "knowledge" based on the data held. The data analysis is entrusted to an expert in research, extraction, processing and representation of the knowledge resulting from the data analysis, which can be identified as a data scientist or data scientist. The data management methodologies are based on techniques deriving from disciplines and techniques from mathematics, statistics, information sciences and computer engineering, and include database management, business intelligence, machine learning and deep learning systems. Technology Intelligence (TI) is based on the research, collection and use of technological information to improve the company's decision-making processes. Therefore the core of TI is represented by the ability to acquire the most useful information for the company for the construction and enhancement of its knowledge. In this sense, the substantial problem is represented by the identification of the information to be considered valid and usable on the knowledge market. Technology Intelligence not only has the task of researching and intercepting information that can make it possible to increase the overall value of the company, but must also pursue the objective of distributing the knowledge produced to the top decision-makers, to the individuals responsible for leading the internal structures and to all those sectors where there is an information need.

Extended Syllabus

DATA SCIENCE

• Models, languages and technologies for data management
• Data analytics and data mining
• Organization and distribution of information within the company
• Information security management
• Infrastructures for storing and transferring digital information

TECHNOLOGY INTELLIGENCE

• Technology Intelligence (TI) concept: enhancement of information to support decision-making processes
• Fundamentals of Technology Intelligence
• Knowledge management: knowledge management
• The cycle of information transfer as a basis for the production of knowledge
• Main methodologies for knowledge acquisition and diffusion
• Information search methodologies
• The Economic Intelligence Process (IE)
• Organization of the Economic Intelligence process in the company
• The production of knowledge:
• Business Intelligence, Analysis Intelligence, Strategic Intelligence
• An information analysis model for IT: the PESTLE model
• Technology Management: technology management
• Competitive Intelligence: managing competitiveness
• Technology Scouting: research and evaluation of innovative technologies
• Strategic Management: the strategic vision
• Innovation management: innovation management
• Market Intelligence: from the analysis of the markets to the types of customers
• Methodologies for the realization of Technology Intelligence
• The Economic Intelligence Process (IE)

Recommended Bibliography

A.Teti, Technology Intelligence. Ottimizzazione delle tecnologie aziendali, Pearson, 2013, pag. 131, EAN: 9788871929507;
A. Teti, Lavorare con i Big Data. La guida completa per il Data Scientist, Tecniche Nuove, pagine 632, Collana, Tecnologie – O’ Reilly, 2017, ISBN: 978-88-481-3154-4

Methods of Provision

Conventional

Teaching Methods

The teaching will take place through frontal teaching divided into theoretical lessons, exercises and seminars.

Evaluation methods

Verification of learning:

The student's level of learning will be assessed with the use of a written test (4 multiple choice questions) and a subsequent compulsory oral test. The duration of this test will depend on the degree of difficulty of the proposed questions and will be communicated during the course. The main objective of the (written) practical test is to probe "knowledge" and "know-how". This represents 80% of the overall evaluation (expressed in thirtieths) articulated in relation to the objectives. Passing the written test will allow access to the oral test.
The oral test (20% of the overall assessment) is aimed at probing communication skills, mastery of the specific technical language of the discipline dealt with, clarity of presentation and interpretation skills.
The examination procedures are the same for attending and non-attending students.

Contacts/More Information

ERASMUS students are invited to contact the teacher for their program. ERASMUS students can discuss the exam in English.

Università degli Studi
"G. d'Annunzio"

Chieti - Pescara

Aree

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