Syllabus - Big Data for Business Analytics PDF

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SYLLABUS 2019/2020

30514 BIG DATA FOR BUSINESS ANALYTICS Classi impartite in lingua inglese Programs: CLEAM (6 crediti - II sem. - OP | 6 cfu - SECS-S/06), CLEF (6 crediti - II sem. - OP | 6 cfu - SECS-S/06), CLEACC (6 crediti - II sem. - OP | 6 cfu - SECS-S/06), BESS-CLES (6 crediti - II sem. - OP | 6 cfu - SECS-S/06), WBB (6 crediti - II sem. - OP | 6 cfu - SECS-S/06), BIEF (6 crediti - II sem. - OP | 6 cfu - SECS-S/06), BIEM (6 crediti - II sem. - OP | 6 cfu - SECSS/06), BIG (6 crediti - II sem. - OP | 6 cfu - SECS-S/06), BEMACS (6 crediti - II sem. - OP | 6 cfu - SECS-S/06) Classes: 31 (II sem.) Department: Decision Sciences Course director: EMANUELE BORGONOVO Classe 31 EMANUELE BORGONOVO Department of Decision Sciences Università Bocconi, Milan, Italy [email protected] FABIO TONOLI Department of Decision Sciences Università Bocconi, Milan, Italy [email protected]

Attenzione! Il programma di seguito riportato è da considerarsi valido SOLO per l'anno accademico 2019/2020.

SUGGESTED BACKGROUND KNOWLEDGE It is suggested for students to have attended a basic course on mathematics and a basic course on statistics before this course.

MISSION The scope of this course is to offer participants a thorough exploration of business analytics and of how computational modelling can be combined with big data to achieve given industry goals. In a well known communication to the European Parliament on 2 July 2014, the European Community evidenced the need of training a generation of managers who know how to combine information derived from data into models to support decisions. In fact, in recent years, the data driven revolution is changing the way in which institutions and corporations make decisions. We

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are heading towards industry 4.0. The great availability of data, the increased computing and information technology capabilities are creating new jobs and changing the way in which companies operate. The February 2018 report of the UK Government Office for Science highlights that computational modelling is a source of competitive advantage for corporations. In the first part of the course, participants are exposed to the fundamental theoretical and methodological basis, analyzing relevant quantitative and mathematical methods. In the second part, students are exposed to industry case studies. With the participation of data scientists and experts coming from the industry participants discover how innovative methods based on big data and information technology have allowed to solve modern industrial problems.

COURSE CONTENT DETAILED - SCHEDULE - CLEAM, CLEF, CLEACC, BESS-CLES, WBB, BIEF, BIEM, BIG, BEMACS cl. 31

Day

Time

Room

Content

Reference

Wednesday 05/02/2020

10.30 - 13.00

Aula B, Piano Introduction to the Notes of the terra, Sarfatti 25 Course Teacher, Vanderbei Ch 12 Big Data and the Principles of Vanderbei, Machine Learning Material from Ch 1 and 2 Introduction to Linear Programming: Geometric interpretation

Monday 10/02/2020

13.00 - 14.30

Aula N39, Piano The simplex 3, Sraffa 13 Method

Wednesday 12/02/2020

10.30 - 13.00

Aula B, Piano Degeneracy and Vanderbei, terra, Sarfatti 25 Unboundedness. Material from Ch Duality 2 and 3, 5

Monday 17/02/2020

13.00 - 14.30

Aula N39, Piano Hands on 3, Sraffa 13 Session

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Vanderbei, Material from Ch 1 and 2

Vanderbei, Material from Ch 2 and 3, 5

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Wednesday 19/02/2020

10.30 - 13.00

Aula B, Piano Sensitivity terra, Sarfatti 25 Analysis

Material Provided by the Teacher

Monday 24/02/2020

13.00 - 14.30

Aula N39, Piano Regressions 3, Sraffa 13

Vanderbei,Materi al from Chapter 12

Wednesday 26/02/2020

10.30 - 13.00

Aula B, Piano Hands on terra, Sarfatti 25 Session

Material Provided by the Teacher

Monday 02/03/2020

13.00 - 14.30

Aula N39, Piano Network Flow 3, Sraffa 13 Problems

Vanderbei, material from Chapters 14 and 15

Wednesday 04/03/2020

10.30 - 13.00

Aula B, Piano Integer Vanderbei, terra, Sarfatti 25 Programming, material from Training a Neural Chapter 23 Network

Monday 09/03/2020

13.00 - 14.30

Wednesday 11/03/2020

10.30 - 13.00

Aula N39, Piano Training a Neural Mafterial 3, Sraffa 13 Network Provided by the teacher Material Given by Aula B, Piano Hands on terra, Sarfatti 25 Session (Network the Teacher flow problems, Integer Programming)

Monday 30/03/2020

13.00 - 14.30

Aula N39, Piano Case Study1 3, Sraffa 13

Use of Big Data and Business Analytics in an Multinational Computer Company

Wednesday 01/04/2020

10.30 - 12.00

Aula B, Piano Case Study1 terra, Sarfatti 25

Use of Big Data and Business Analytics in an Multinational Computer Company

Monday 06/04/2020

13.00 - 14.30

Aula N39, Piano Case Study 1 3, Sraffa 13

Use of Big Data and Business Analytics in an Multinational Computer Company

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Wednesday 08/04/2020

10.30 - 12.00

Aula B, Piano Case study 2 terra, Sarfatti 25

Use of Big Data in a Technology Environment, Michael Taylor, Head of Data Science Siemens

Monday 20/04/2020

13.00 - 14.30

Aula N39, Piano Case study 2 3, Sraffa 13

Use of Big Data in a Technology Environment, Michael Taylor, Head of Data Science Siemens

Wednesday 22/04/2020

10.30 - 12.00

Aula B, Piano Case study 3 terra, Sarfatti 25

Use of Big Data in a Technology Environment, Michael Taylor, Head of Data Science Siemens

Monday 27/04/2020

13.00 - 14.30

Aula N39, Piano Case study 3 3, Sraffa 13

Use of Big Data in a Technology Environment, Michael Taylor, Head of Data Science Siemens

Wednesday 29/04/2020

10.30 - 12.00

Aula B, Piano Case study 4 terra, Sarfatti 25

Optimizing Energy Consumption Thorugh Data Managements: the case of a Large Store

Monday 04/05/2020

13.00 - 14.30

Aula N39, Piano Case study 4 3, Sraffa 13

Optimizing Energy Consumption Thorugh Data Managements: the case of a Large Store

Wednesday 06/05/2020

09.00 - 13.00 Course Closing at SIEMENS

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Workgroup Presentations

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TEACHING METHODS Selection: Face-to-face lectures face-to-face lectures Guest speaker's talks (in class or in distance) in-class in distance Case studies /Incidents (traditional, online) traditional case studies

The course will make use of a combination of teaching techniques. Face-to-face lectures will be used for the sessions in which methodological and theoretical parts of the paper are proposed and discussed. In these sessions students will be assisted in identifying the quantitative model, in implementing the model through dedicated software and in performing sensitivity analysis. In the second part of the course, students will be exposed to the solution of industry case studies presented in a triplet of lectures. After the exposition by the experts of the industrial problem, participants will be introduced to the methods of solution and will be guided in critically discussing the results, the methodologies adopted and in identifying weaknesses and remaining open questions.

ASSESSMENT METHODS Selected methods:

Continuous assessment

Partial exams

General exam

x

x

x

x

Written individual exam (traditional/online) Closed answers questions exam (e.g.:

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single input, multiple choice, select etc.)

April 22, 2020

As you know at the times we modified the exam rules there was still hope that the exams could be taken in Bocconi. This possibility has been canceled by the evolution of the crisis, unfortunately. Bocconi foresee that a portion of the exam has to be taken with your pc, using a software called Respondus. Here are the new detailed rules. Exam date of May 26, Multiple-Assignment mode A third quantitative assignment (24 points maximum) will be launched the week of May 6th and stay live for 24 hours. The assignment will concern the first part of the course. If you do this assignment you can access the Respondus exam part bringing with you the points accumulated with the multiple assignments (28 points maximum). On May 26, the Respondus exam will consist of a set of qualitative questions (multiple choice) that will count for a maximum of 5 additional points. The qualitative questions will concern both the first and second part of the course. It will be made of 5 questions: Letting 100% the total score, each correct answer will be worth +10% (1 point) and each wrong answer will count for -5% (-0.5 points). Exam date of May 26, Single-Assignment mode You discard the points you have accumulated in the three quantitative assignments (max 28 pts). A quantitative assignment (26 points maximum) will appear the day before the exam (May 25th) and stay live from 8:30 am Milan time to 12:00 p.m (midnight). On May 26, the Respondus exam will consist of a set of qualitative questions (multiple choice) that will count for a maximum of 5 additional points. It will be made of 5 questions: letting 100% the total score, each correct answer will be worth +10% and each wrong answer will count for -5%. When can you choose? You can choose after the third assignment. We plan to have the third assignment during the week of May 6th, thus leaving you time to decide before the final enrollment date for the first exam date (appello) of May 26. If you are satisfied with the score you totaled with the three assignments, you keep it and move on to the final Respondus exam. If you are not satisfied, you just opt for enrolling for the “single assignment mode”. If you do so, you will then have to take the “single assignment” the day before the exam date. Note: in the assignments, questions will be randomized and personalized, so that numerical answers in each of your tests will be different, while guaranteeing full homogeneity in the level of difficulty. Exam dates after the May 26 date (namely, June 18 and September 04). A quantitative assignment (26 points) will be launched the day before the exam date (namely, June 17 and September 03), from 8:30 a.m. to 8:30 p.m. Milan time and will be live for 12 hours. On the exam date, you will take the Respondus part, with the same points discussed above.

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Below are the exam dates and the enrollment dates: Exam Date

Enrollment Date

1

26/05/2020

20/05/2020

2

18/06/2020

12/6/2020

3

4/9/2020

31/08/2020

----- Previous Change --March 11, 2020: Following the University guidelines related to the current CoronaVirus emergency, the following adjustments to the exam rules have been made.

The group works, which have become infeasible in the current situation, are replaced by two online assignments. The two online assignments are worth a maximum of 2 points each, for a total of 4 points. These points add to the score you will earn with the final exam. The final exam is worth 31 points. The first assignment will be similar in structure to the first midterm that we would have had. Thus, you can consider the midterm of March 23 2019, available on the web. But also exercises from all past exams are helpful as well as the other exercises and end of class quizzes. The first assignment will be available on March 23 2020 at 8:30 Milan time. It will remain open until March 24 2020 at 20:30, Milan time. So, it will be open for about 36 hours. Then, once you start it, you will have 90 minutes. The second assignment will be opened later during the course and will concern the training of a neural network. It will also be available online with a modality similar to the first assignment. The assignments are individual and the rules of the honor code apply. Of course, it is an open book exam. The purpose of the assignments is to allow you to earn extra points. Potentially, your final score in the course could go up to 35 (31 in the final + 4 in the assignments). So, no penalty for not doing them.

Regarding the final exam, the following applies. The final exam will cover the entire material explained in the course. It will be worth 31 points.

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The following logistic items apply at the moment, but may be subject to changes: 1) The final exam will be in Bocconi computer rooms, on virtual machines carrying all necessary software; 2) On the exam date, depending on the number of enrolled students, there might be more than one shift. Then, the first shift will be on the time indicated by Your agenda. The second shift will start 2 hours later. 3) After the exam, Your test will be permanently visible in Blackboard, under MyGrades. In the case of questions concerning the exam, please write within 3 working days from the exam date to the Help&Desk of the Department of Decision Sciences. All queries will be examined, if on time. It will not be possible to consider queries submitted later than 3 working days from the exam date.

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Students can chose to take either a final general written exam or the combination of a partial exam and a work group. The partial exam will cover the first part of the course, with a maximum score of 21 points. The work group will have a maximum score of 10 points and will be about the solution of a business case related to the material introduced in the second part of the course. The general written exam will cover the entire course material, with a prevalence of problems written in a mathematical form, and will correspond to a total of 31 points. ---------

TEACHING MATERIALS - CLEAM, CLEF, CLEACC, BESS-CLES, WBB, BIEF, BIEM, BIG, BEMACS cl. 31 Teaching material is composed of: 1) The textbook

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2) The class slides provided by the teacher 3) The dedicated video tutorials 4) End of class quizzes 5) Exercised and past exams All the material is available through the blackboard platform.

HONOR CODE Bocconi University conceives of education as an ongoing process that stretches across a person’s entire professional life. The University hopes that the entire Bocconi community will respect the values of fairness and correctness associated with it, values which inspire and guide the conduct of all community members as they pursue common objectives and a shared mission. The Bocconi University Honor Code is published at http://www.unibocconi.eu/honorcode. We encourage all students to read it.

COURSE ETIQUETTE

Students are required to comply with the course etiquette and to respect Bocconi honor code.

Aggiornato al 26/01/2020 17:15

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