WebHome < BI

%DASHBOARD{ section="dashboard_start" }%<br />%DASHBOARD{ section="banner" image="%ATTACHURL%/business-intelligencenew.jpg" width="736" height="278" style="center"}%

---+++ [[https://www.google.it/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&ved=0ahUKEwiyxYjx5MXXAhUHmrQKHeEVBpsQFgg5MAA&url=http%3A%2F%2Ftwiki.di.uniroma1.it%2Ftwiki%2Fview%2FBI%2FWebHome&usg=AOvVaw3wzojDORwECDE_vzI51s3z][WebHome &lt; BI &lt; TWiki]]

<br />%DASHBOARD{ section="box_start" title="Overview"}%
---+ 

Presentation of the course [[%ATTACHURL%/CourseIntroductionandObjectives.pdf][CourseIntroductionandObjectives.pdf]] [[%ATTACHURL%/CourseIntroductionandObjectives-1.pdf][<br />]]

Enterprises today are driven by data. "<i>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</i>" (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
%DASHBOARD{ section="box_end" }%%DASHBOARD{ section="box_start" title="Schedule and Exams (read carefully!)"}%

*Class days (2023-24)*

Classes have started on<b>%RED% Monday September 18th%ENDCOLOR%</b>, 2023 (see schedules on the MANIMP 23-24 web site) %RED% *Monday 12:00-14:00 8b; Tuesday 16:00-18:00 Lab Info; Wednesday 14:00-16:00 9A* %ENDCOLOR%
---+ NOTE: MONDAY , September 25th THERE WILL BE NO LESSON

*It is highly recommended to attend the classes in presence unless you are residing in another region or country. Interactivity is not allowed by the Faculty for security reasons to remote students.*

Monday 11-13 (8a), Wednesday 14-16 (8a), Thursday 16-18 (Didalab)
   * PART A: September-mid November (Prof. Paola Velardi)
   * PART B: mid November-December (Prof. Paolo Gaspare Bottoni)
   * LAB: During PART A, about 7 lessons will be held in the laboratory (LabInfo) for practical applications using [[https://www.ibm.com/cloud/watson-studio/details][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 [[%ATTACHURL%/Instruction_for_the_Business_Intelligence_project_2022-23.pdf][Instruction_for_the_Business_Intelligence_project_2022-23.pdf]] for creating your project. Projects should be submitted by teams of two. You can submit your project alone if you can't find a classmate, but no extra grades will be assigned for projects authored by a single student.
   * 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

---++++ Project delivery deadlines: Winter %RED%2024%ENDCOLOR%: January 7th (january session), January 30th (February session); %RED%Summer 2023%ENDCOLOR%: June 5th (June session); July 5th (July session); September 1st (September session)

*%RED%Projects delivered after the deadline will NOT be corrected. %ENDCOLOR%*

---++++ *Exam PART B rules:*
   * Project on a selected business process using process modelling and simulation tools. Projects can be submitted by teams of up to five members (after approval by Professor Bottoni for groups of 4 or 5).
*The final grade* is the weighted sum of BI (2/3) and BPM (1/3) grades.

<b>IMPORTANT: </b>INFOSTUD *sessions* have a start date and an end date. This is because I can't register a grade until you 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.<b> THIS IS NOT the date of the test!</b> Usually, there are two test dates within any session, but you need to register on INFOSTUD much earlier (e.g., may-early june for the june-july 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.

<br />%DASHBOARD{ section="box_end" }%%DASHBOARD{ section="box_start" title="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
%DASHBOARD{ section="box_end" }%%DASHBOARD{ section="box_start" title="Part A: Course Material"}%
---++ *IMPORTANT NOTES:*
   * *Subscribe* to Google Group (Prof. Velardi) [[https://groups.google.com/a/di.uniroma1.it/g/businessintelligence23-24][Business Intelligence Google Group 2023-2024]] SUBSCRIBE WITH YOUR INSTITUTIONAL SAPIENZA EMAIL (otherwise you will not be accepted)
   * *LABS*: 7 labs on Watson Studio will be held starting on October. Details in class.
---+++ List of topics and slides (do not download until updated 23):
   * Topic 1 (updated 23) - What is Business Intelligence [[%ATTACHURL%/1.WhatIsBI.pptx][1.WhatIsBI.pptx]] [[%ATTACHURL%/1b.WhatIsBI.pptx][1b.WhatIsBI.pptx]] [[%ATTACHURL%/1c._BI_project_workflow.pptx][1c._BI_project_workflow.pptx]] [[%ATTACHURL%/1.WhatIsBI.pptx][<br />]]
   * Topic 2 (updated 23) - Basic notions of databases and data schemas. What types of data and what for? Storing and integrating data in Data Warehouses: Extraction, Transformation and Load [[%ATTACHURL%/2.DataWarehousesETL.pptx][2.DataWarehousesETL.pptx]] [[%ATTACHURL%/2.DataWarehousesETL.pdf][2.DataWarehousesETL.pdf]] [[%ATTACHURL%/2.DataWarehousesETL.pptx][<br />]]
   * Topic 3 (updated 23)- Data Warehouses: Data Structures and Operations [[%ATTACHURL%/3.DW-datastructuresandprocessing.pptx][3.DW-datastructuresandprocessing.pptx]] [[%ATTACHURL%/3.DW-datastructuresandprocessing.pdf][<br />]]
   * Topic 4 - (updated 23) Data Analytics [[%ATTACHURL%/4.DataAnalytics.pptx][4.DataAnalytics.pptx]], [[%ATTACHURL%/4.DataAnalytics.pdf][4.DataAnalytics.pdf]]
   * Topic 5 (updated 23)- Social Analytics : [[%ATTACHURL%/5.SocialMediaAnalytics2023.pptx][5.SocialMediaAnalytics2023.pptx]] [[%ATTACHURL%/5.SocialMediaAnalytics2023.pdf][5.SocialMediaAnalytics2023.pdf]] [[%ATTACHURL%/5.SocialMediaAnalyticsshort.pptx][<br />]]
   * Topic 6 - (updated 2023) Data Visualization, Query and Reporting [[%ATTACHURL%/6.DataVisualization2023.pdf][6.DataVisualization2023.pdf]] Here you can find a master thesis by one of the course students: [[%ATTACHURL%/How_data_visualization_can_help_business_growth.pdf][How_data_visualization_can_help_business_growth.pdf]]
   * (2023) Labs on *IBM Watson Studio* (cloud application): Labs slides and data are on Google Drive shared with google group. [[%ATTACHURL%/Lab6_2018.pptx][<br />]]

<b> %DASHBOARD{ section="box_end" }%%DASHBOARD{ section="box_start" title="Part B: Process Modeling"}%</b>
---++ *IMPORTANT NOTES:*

Subscribe to the Google Group of BI / Process Modeling (Prof Bottoni) using your institutional address (domain: <u>@studenti.uniroma1.it</u>): <a href="https://groups.google.com/g/bpmbottoni" target="_blank">https://groups.google.com/g/bpmbottoni</a>. Teaching material will be posted on a [[https://drive.google.com/drive/u/0/folders/0B971bP7lYTQ1NzFORzJ0S1FFUkE][dedicated remote Google Drive folder]]. The subscription to the Google Group automatically grants you access to those resources.

<a href="https://www.visual-paradigm.com/" target="_blank">Visual Paradigm</a> provides Sapienza University of Rome with <a href="https://www.visual-paradigm.com/features/uml-and-sysml-tools/" target="_blank">UML</a> and <a href="https://www.visual-paradigm.com/features/bpmn-diagram-and-tools/" target="_blank">BPMN</a> tools under the <a href="https://www.visual-paradigm.com/partner/academic/" target="_blank">Academic Partner Program</a>.

---+++ List of topics and resources

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)

Exams on the BPM part are by appointment. Deadlines for submitting your material are the same as those set by Professor Velardi.

%DASHBOARD{ section="box_end" }%%DASHBOARD{ section="box_start" title="Use cases, datasets and readings" }%
---+++++ Open Data sources for Business Intelligence and Business Process Intelligence
   * [[https://communities.sas.com/t5/SAS-Communities-Library/Need-data-for-teaching-or-learning-Get-it-here/ta-p/221088][Data resources for BI: a very large catalogue of freely available datasets]]
   * [[https://www.sisense.com/blog/free-data-sources-upgrade-business-decision-making/][Another pointer to open data sources]] for business intelligence
   * The Business Process Intelligence Challenge event logs and other real-world process data: <a href="https://www.tf-pm.org/resources/logs" target="_blank">https://www.tf-pm.org/resources/logs</a>
   * Google has released a search engine to search for datasets: <a href="https://toolbox.google.com/datasetsearch" target="_blank">https://toolbox.google.com/datasetsearch</a>
---++++ Case studies
   * [[http://www.teradata.com/Resources?AssetType=Case+Studies][Teradata case studies ]]
   * [[https://www.sas.com/en_us/insights/business-intelligence.html][SAS case studies]]
   * [[http://ideal-analytics.com/resources/case-studies/][Ideal Analytics case studies]]
   * Process mining case studies: <a href="https://www.tf-pm.org/resources/casestudy" target="_blank">https://www.tf-pm.org/resources/casestudy</a>
   * Some specific use cases:
      * [[%ATTACHURL%/ColdChainAnalyticsMagpieSensing.pdf][ColdChainAnalyticsMagpieSensing.pdf]]
      * [[%ATTACHURL%/Isle-of-Capri-Casinos.pdf][Isle-of-Capri-Casinos.pdf]]
      * [[%ATTACHURL%/RedCrossDutchcasestudy.pdf][RedCrossDutchcasestudy.pdf]]
      * [[%ATTACHURL%/InternetofTrainsSiemens.pdf][InternetofTrainsSiemens.pdf]]
      * [[%ATTACHURL%/BouyguestelecomdataWharehouse.pdf][BouyguestelecomdataWharehouse.pdf]]
      * [[%ATTACHURL%/Thomposn-news-analytics.pdf][Thomposn-news-analytics.pdf]]
---++++ Readings
   * Three readings on Data Analytics methods for Business Applications:
      * Finance [[%ATTACHURL%/DataMiningforFinancialApplications.pdf][DataMiningforFinancialApplications.pdf]]
      * Customer Segmentation: [[%ATTACHURL%/ClusteringforMarketSegmentation.pdf][ClusteringforMarketSegmentation.pdf]]
      * Fraud Detection: [[%ATTACHURL%/FraudDetectionAnalytics.pdf][FraudDetectionAnalytics.pdf]]
   * [[http://searchbusinessanalytics.techtarget.com/ehandbook/Machine-learning-technology-techniques-add-new-analytics-smarts][Get a grasp of Machine Learning methods and applications]]
   * From data to decisions: BI management frameworks and examples [[%ATTACHURL%/FromDatatoDecisions-LESSONSFROMREALUSECASES.pdf][FromDatatoDecisions-LESSONSFROMREALUSECASES.pdf]]
   * The process mining manifesto: <a href="https://www.tf-pm.org/resources/manifesto" target="_blank">https://www.tf-pm.org/resources/manifesto</a>

%DASHBOARD{ section="box_end" }%%DASHBOARD{ section="dashboard_end" }%
This topic: BI > WebHome
Topic revision: r173 - 2023-11-12 - PaolaVelardi