Tags:
create new tag
view all tags

WebHome < BI < TWiki


Overview

IMPORTANT: please read carefully all emails sent to the Google group. You will find precise indications on how to connect via zoom. Students willing to assist in presence need to adopt general rules published by Sapienza. It is highly recommended that you bring your computer in class.

Presentation of the course CourseIntroductionandObjectives.pdf

Enterprises today are driven by data. "Business Intelligence allows people of all levels in organizations to access, interact with, and analyze data to manage the business, improve the performance, discover opportunities, and operate efficiently" (Cindi Howson, Successful BI, McGrawHill).

However, the degree to which BI solutions can be successfully adopted within organizations depend to a great extent on the degree to which business and IT experts can partner together. The objective of this course is to form Advanced Business Users of BI applications, with a deep understanding of the business needs and a good understanding of technology. The Advanced Business User understands the business and how to leverage technology to improve it, leads the interpretation of business requirements and strategic objectives, and helps designing reports to answer business questions.

The course is in two parts:

  • PART A: Business Intelligence and Social Analytics 6CFU Instructor: Prof. Paola Velardi velardi AT di.uniroma1.it
  • PART B: Process mining 3CFU Instructor: Prof. Claudio Di Ciccio diciccio AT di.uniroma1.it
Schedule and Exams (read carefully!)

Class days (2020):

Monday 11-13, Tuesday 16-18, Thursday 16-18

  • PART A: September-mid November (Prof. Paola Velardi)
  • PART B: mid November-December (Prof. Claudio Di Ciccio)
  • LAB: During PART A, about 8 lessons will be held in the laboratory (year 2019: Ground Floor Lab) for practical applications using IBM Watson Studio in cooperation with IBM tutors.
Exam PART A rules:
  • Written test: 60%
  • Project on selected business problems using Watson Studio: 40%. Please follow carefully GuidelinesBproject.pdf for creating your project. Projects can be submitted by teams of two.
  • Interactive students, who read and present selected topics assigned by the instructor (either in class, or remotely, sending a registered presentation) may increase 1-2 points the final grade.
Exam PART B rules:
  • Written test: 60%
  • Project on a selected business process using process modelling, simulation and mining tools: 40%. Projects can be submitted by teams of four. The guidelines will be published soon!
  • Interactive students, who read and present selected topics assigned by the instructor (either in class, or remotely, sending a registered presentation) may increase the final grade by up to 2 points.
The final grade is the weighted sum of BI (2/3) and BPM (1/3) grades.

IMPORTANT: INFOSTUD sessions have a start date and an end date. This is because I can't register a grade until you don't pass the test, and deliver the BI and BPM projects. So, there is not one single date I can establish. Usually, you can only see the start date of an exam session on Infostud. THIS IS NOT the date of the test! Usually, there are two test dates within any session. You can register for a test through the Google form I circulate before any test date. Please remember to register on Infostud IF you believe that during the session (winter or summer) you will be able to obtain a final grade - based on the result of a test, and the 2 projects.

ERASMUS STUDENTS: depending on the signed learning agreement, some Erasmus students may attend only the BI part (6 credits) and obtain a grade for this part of the course. However, these students must show their learning agreement to prove that they only need 6 CFU.


Suggested Text Books
PART A
  • Cindi Howson "Successful Business Intelligence" Second Edition, Mc Graw Hill
  • Ramesh Sharda, Dursun Deelen and Efraim Turban "Business Intelligence: A Managerial Perspective on Analytics" Third Edition, Pearson
  • Rick Sherman "Business Intelligence Guidebook" Morgan Kauffmann
  • Course slides and use cases
PART B

  • M. Dumas, M. La Rosa, J. Mendling, H. A. Reijers, Fundamentals of Business Process Management, Springer, 2018 (the first edition from 2013 would work too)
  • W. van der Aalst, Process Mining - Data Science in Action, Second Edition. Springer, 2016 (the first edition from 2011 would work too)
  • Course slides
Part A: Course Material

IMPORTANT NOTES:

  • Subscribe to Google Group (Prof. Velardi) Business Intelligence 20-21 on Google Groups
  • NOTE: Lessons will regularly start on Thursay 24rd.
  • LABS: 8 labs on Watson Studio will be held starting on October. Details in class.

List of topics and slides (TBU = slides To be Updated, do not download until updated):

Part B: Business Process Intelligence

IMPORTANT NOTES:

Subscribe to the Google Group of BI / Process Mining (Prof Di Ciccio) using your institutional address (domain: @studenti.uniroma1.it): https://groups.google.com/a/uniroma1.it/g/bi--process-mining/

List of topics and resources

This part of the course will be assessed through a written test and a teamwork assignment on business process intelligence.

Topics:

  • Introduction to Business Process Modeling
  • Formal models and standards for Business Process Models
  • Process simulation and analytics (and dedicated software tools)
  • Process mining: automated discovery and conformance checking (and dedicated software tools)
  • Recent advancements on process automaton: an introduction to blockchain-based process execution
Use cases, datasets and readings
Open Data sources for Business Intelligence and Business Process Intelligence

Case studies

Readings

Topic attachments
I Attachment History Action Size Date Who Comment
PDFpdf 1.WhatIsBI.pdf r3 r2 r1 manage 13927.2 K 2020-09-04 - 14:04 PaolaVelardi  
PowerPointpptx 1.WhatIsBI.pptx r4 r3 r2 r1 manage 8961.0 K 2020-09-04 - 14:04 PaolaVelardi  
PDFpdf CourseIntroductionandObjectives.pdf r2 r1 manage 316.4 K 2020-09-28 - 13:20 ClaudioDiCiccio  
Edit | Attach | Watch | Print version | History: r116 < r115 < r114 < r113 < r112 | Backlinks | Raw View | Raw edit | More topic actions
Topic revision: r116 - 2020-11-23 - PaolaVelardi






 
Questo sito usa cookies, usandolo ne accettate la presenza. (CookiePolicy)
Torna al Dipartimento di Informatica
This site is powered by the TWiki collaboration platform Powered by PerlCopyright © 2008-2020 by the contributing authors. All material on this collaboration platform is the property of the contributing authors.
Ideas, requests, problems regarding TWiki? Send feedback