Text Text. Wil van der Aalst Professor Information Systems TU/e

Transcription

1 Text Text Wil van der Aalst Professor Information Systems TU/e

2 A new profession is emerging, just like computer science in the early 1980-ties! Industry and Society need Data Scientists! t

3 t

4 EIT-Digital Data Science Major 5 universities involved

5 EIT-Digital Data Science Major 3 entry universities

6 EIT-Digital Data Science Major 5 exit universities (specializations)

7 EIT-Digital Data Science Major 5 specializations Process Mining in High Tech Systems, Healthcare, Visual Analytics, or Big Software at TUE Distributed Systems & Data Mining for Really Big Data at KTH Design, Implementation, and Usage of Data Science Instruments at TUB Internet of Things (IoT) at UPM Multimedia & Web Science for Big Data at UNS

8 Statistics on the first intake Total number of students: 46 EU students 54% Age :20-29 Female students: 17% DSC

9 t DSC/e

10 t Data Science Center Eindhoven

11 DSC/e: Competences and Research Programs 28 groups and 420+ people involved Analysis: How to turn data into real value (models, answers/decisions, and visualizations/insights)? Probability and Statistics Enabling technologies: How to get the data and deal with computational/ infrastructural challenges (big data and hard questions)? Internet of Things Large-Scale Distributed Systems Data-Intensive Algorithms Data Mining Stochastic Networks Process Mining Visualization [RP1] Process Analytics: Improving Service While Cutting Costs [RP2] Customer Journey: Correlating Events to Learn and Influence Customer Behavior Context: Why are we using data science, does it have the intended effect, and will people accept it? [RP3] Smart Maintenance & Diagnostics: Safeguarding Availability Human and Social Analytics [RP4] Quantified Self: Improving Performance and Well-Being Privacy, Security, Ethics, and Governance [RP5] Data Value Data-Driven and Operations Privacy: Economic and Legal Management Aspects of Data Science Data-Driven Innovation and Business [RP6] Smart Cities: Ensuring Safety and Convenience for Citizens [RP7] Smart Grids: Data Intensive Infrastructures 11

12 Data Science Flagship (Philips & DSC/e) 4 Strategic topics Data Driven Value Propositions Healthcare Smart Maintenance Optimizing Healthcare Workflows Continuous Personal Health 4 TU/e departments 16 PhD students 30 Data science specialists Many more organizations BrandLoyalty Vanderlande Industries ASML SynerScope Magnaview Fluxicon Adversitement Rabobank ING SAP IBM PwC AMC

13 Process Mining

14 Example: Process Mining as the Bridge Between Data Science and Process Science

15 Process Mining: Spreadsheet for behavior row = event resource Input: events ( things that have happened ) Mandatory per event: Optional case identifier activity name timestamp/date resource transaction type costs case identifier activity name timestamp

16 Process Mining: Spreadsheet for behavior 208 cases 5987 events 74 activities

17 Process Mining: Spreadsheet for behavior batching for activities opstellen eindnota and archiveren

18 Loesje van der Aalst desire line Process Discovery

19 Process Mining: Spreadsheet for behavior process discovery NO modeling needed!

20 Process Mining: Spreadsheet for behavior process discovery NO modeling needed! 74 act. 11 act. 3 act.

21 process model event data Conformance Checking

22 desire line very safe system Conformance Checking

23 Process Mining: Spreadsheet for behavior conformance checking? discovered or hand-made

24 Process Mining: Spreadsheet for behavior conformance checking fitness of 93.5%

25 Process Mining: Spreadsheet for behavior conformance checking final inspection is skipped 40 times

26 Process Mining: Spreadsheet for behavior conformance checking move on model (something should have happened, but did not) move on log (something happened that should not happen)

27 Process Mining: Spreadsheet for behavior performance analysis NO modeling needed! average flowtime is 1.92 months bottleneck

28 Process Mining: Spreadsheet for behavior performance analysis waiting time of days NO modeling needed!

29 Process Mining: Spreadsheet for behavior NO modeling needed! animating reality real cases

30 Process Mining: Spreadsheet for behavior animating reality 16 cases are queueing

31 Process Mining: Spreadsheet for behavior What? Deviations Where? Why? time costs

32 Conclusion Need for Data Scientists! Wonderful Data Science Master Program with 3 entry points and 5 specializations Ask Farideh Heidari (f.heidari@tue.nl) for details! Zoomed-in on the Data Science ecosystem in Eindhoven: Data Science Center Eindhoven (DSC/e) Zoomed-in on a particular Data Science topic: Process Mining (linking processes and data) 32

33 masterschool.eitdigital.eu More information?