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INTRODUCTION TO DATA ANALYTICS

CODE 98238
ACADEMIC YEAR 2022/2023
CREDITS
  • 6 cfu during the 3nd year of 10716 INGEGNERIA GESTIONALE (L-9) - GENOVA
  • SCIENTIFIC DISCIPLINARY SECTOR ING-INF/05
    LANGUAGE Italian
    TEACHING LOCATION
  • GENOVA
  • SEMESTER 1° Semester
    TEACHING MATERIALS AULAWEB

    OVERVIEW

    The course introduces the basic techniques for the representation and exploratory analysis of data from a Business Intelligence perspective, with reference to descriptive analytics and exploratory data analysis methodologies aimed at supporting decisions in industrial and management fields.

    AIMS AND CONTENT

    LEARNING OUTCOMES

    The aim of the course is to introduce the student to the fundamental concepts related to EDA (exploratory data analysis) using the Python language as a tool and, in particular, the components of the SciPy library for statistical processing and data visualization. The course will provide knowledge on the main EDA techniques from a theoretical point of view and will develop the practical part by introducing the related SciPy constructs for data analysis and visualization. As part of the course, the student will acquire the skills to design and create simple applications for dashboard design and allow the analysis and representation of data from different sources. The student will develop the ability to choose the best approaches in relation to the particular data processed and the task to be performed.

    AIMS AND LEARNING OUTCOMES

    The student will be able to design and build a simple dashboard using data from different sources.

    PREREQUISITES

    Python programming language

    Main concepts of databases

    TEACHING METHODS

    Theoretical classes and PC labs

    SYLLABUS/CONTENT

    Introduction to EDA (Exploratory Data Analysis)

    Structured and unstructured data

    Data preprocessing and Data wrangling

    Key Performance Indicators

    Date visualization

    Dashboard design

    Data warehousing and OLAP

    Data Quality

    Data Privacy

    RECOMMENDED READING/BIBLIOGRAPHY

    Material provided by the teacher

    Python libraries: SciPy https://scipy.org and in particular the Pandas library https://pandas.pydata.org

    Optional material:

    C.C Aggarwal, Data mining: the textbook. Springer, 2015. [Chap.2,3]
    J.V. Guttag, Introduction to computation and programming using Python. MIT Press, 2013. [Chap. 16]
    M.J.Zaki, M.Wagner Jr., Data Mining and Machine Learning: Fundamental Concepts and Algorithms. Cambridge University Press, 2019. [Chap. 1-7]
    S.Few, Information Dashboard Design, 2nd Ed., Analytics Press, 2013.
    D. Parmenter, Key Performance Indicators, 2nd Ed., 2010.
    W. McKinney et al., Pandas: powerful Python data analysis toolkit, 2021

    TEACHERS AND EXAM BOARD

    Exam Board

    DAVIDE ANGUITA (President)

    ALBERTO OLIVERI

    FABIO ROLI

    LUCA ONETO (President Substitute)

    LESSONS

    Class schedule

    All class schedules are posted on the EasyAcademy portal.

    EXAMS

    EXAM DESCRIPTION

    The student will develop independently (individually or in cooperation with other students) a case study of their choice, among those proposed by the teacher, using one of the methodologies illustrated during the course. The oral exam will focus on the discussion of the case study.

    ASSESSMENT METHODS

    The oral exam will allow to verify the ability to analyze and represent a set of data from different sources in order to make them usable by a hypothetical end user identified with the case study.

    Exam schedule

    Date Time Location Type Notes
    23/12/2022 08:00 GENOVA Esame su appuntamento L'esame deve essere prenotato tramite email a davide.anguita@unige.it Leggete attentamente le istruzioni su AulaWeb
    23/12/2022 08:00 GENOVA Orale L'esame deve essere prenotato tramite email a davide.anguita@unige.it Leggete attentamente le istruzioni su AulaWeb
    17/01/2023 08:00 GENOVA Esame su appuntamento L'esame deve essere prenotato tramite email a davide.anguita@unige.it Leggete attentamente le istruzioni su AulaWeb
    17/01/2023 08:00 GENOVA Orale L'esame deve essere prenotato tramite email a davide.anguita@unige.it Leggete attentamente le istruzioni su AulaWeb
    15/02/2023 08:00 GENOVA Esame su appuntamento L'esame deve essere prenotato tramite email a davide.anguita@unige.it Leggete attentamente le istruzioni su AulaWeb
    15/02/2023 08:00 GENOVA Orale L'esame deve essere prenotato tramite email a davide.anguita@unige.it Leggete attentamente le istruzioni su AulaWeb
    31/05/2023 08:00 GENOVA Esame su appuntamento L'esame deve essere prenotato tramite email a davide.anguita@unige.it Leggete attentamente le istruzioni su AulaWeb
    31/05/2023 08:00 GENOVA Orale L'esame deve essere prenotato tramite email a davide.anguita@unige.it Leggete attentamente le istruzioni su AulaWeb
    19/06/2023 08:00 GENOVA Esame su appuntamento L'esame deve essere prenotato tramite email a davide.anguita@unige.it Leggete attentamente le istruzioni su AulaWeb
    19/06/2023 08:00 GENOVA Orale L'esame deve essere prenotato tramite email a davide.anguita@unige.it Leggete attentamente le istruzioni su AulaWeb
    21/07/2023 08:00 GENOVA Esame su appuntamento L'esame deve essere prenotato tramite email a davide.anguita@unige.it Leggete attentamente le istruzioni su AulaWeb
    21/07/2023 08:00 GENOVA Orale L'esame deve essere prenotato tramite email a davide.anguita@unige.it Leggete attentamente le istruzioni su AulaWeb
    12/09/2023 08:00 GENOVA Esame su appuntamento L'esame deve essere prenotato tramite email a davide.anguita@unige.it Leggete attentamente le istruzioni su AulaWeb
    12/09/2023 08:00 GENOVA Orale L'esame deve essere prenotato tramite email a davide.anguita@unige.it Leggete attentamente le istruzioni su AulaWeb