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Overview

Presentation of the course CourseIntroductionandObjectives-1.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 modeling 3CFU Instructor: Prof. Paolo Bottoni bottoni AT di.uniroma1.it
Schedule and Exams
Class days (2018):

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

  • PART A: September-November (Prof. Paola Velardi)
  • PART B: November-December (Prof. Paolo Bottoni)
  • LAB: During PART A, about 8 lessons will be held in the laboratory (year 2018: Didalab) for practical applications using IBM Watson Analytics, in cooperation with IBM tutors.
Exam PART A:
  • Written test: 50%
  • Project on selected business problems using Watson Analytics: 50%. Please follow carefully GuidelinesBproject.pdf for creating your project. Projects can be submitted by teams of two - three is also ok, but I expect something more.

Exam Part B: BPM Project

NOTE: joint projects with Computer Science students attending the "Machine Learning" course (Master in Computer Science) are possible for selected students

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, 2013
  • W. van der Aalst, K. Van Hee, Workflow Management: Models, Methods, and Systems, MIT Press, 2004
  • M. Weske, Business Process Management. Concepts, Languages, Architectures, Springer, 2012
  • Course slides
Part A: COURSE MATERIALS

IMPORTANT NOTES:

  • Subscribe to Google Group (Prof. Velardi) Business Intelligence 2019 on Google Groups
  • NOTE: Lessons will regularly start on Monday 17th.
  • LABS : From Thursday 27th and until November, Thursday 15, Thursday's lessons will be held in DIDALAB, 1st floor, sector C. Please obtain credentials BEFORE first lab (see how in first Lab's slides).

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

Part B (Prof. Bottoni)

Visual Paradigm supports Sapienza University of Rome with UML tools and ERD tools under the Visual Paradigm Academic Training Partner Program.

The module provides an introduction to the main concepts, models, languages and tools relative to Business Process and Workflow Management.

Subscribe to Google Group (Prof. Bottoni) BPMBottoni

This part of the course will be assessed through the presentation of work based on a case study described here

Topics:

Topic 1: Introduction to Business Process Modeling

a. General view of modeling

b. General notion of process

c. Modeling of control flow, data flow, resource allocation

Lesson1Introduction.pdf

Topic 2: Formal models and standards for Business Process

a. BPDM

b. BPMN Lesson2IntroductionToBPMN.pdf Lesson5AdvancedBPMModeling.pdf Lesson6Coreographies.pdf

Topic 3: Workflow patterns

a. Flow patterns

b. Resource patterns

Topic 4: The process-modeling process

a. Process identification Lesson3ProcessIdentification.pdf

b. Process discovery Lesson4ProcessDiscovery.pdf

b. Process analysis

b1. Qualitative Lesson7Qualitative.pdf

b2. Quantitative Lesson8Quantitative.pdf Lesson9QuantitativeQueue.pdf

d. Process re-design Lesson10ProcessRedesign.pdf

e. Process mining Lesson11ProcessMining.pdf

Topic 5: Tools for Business Process and Workflow Management

a. Visual paradigm

b. YAWL

c. Signavio

Use cases, datasets and readings (PART A)
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Topic revision: r74 - 2018-11-22 - PaoloBottoni





 
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