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Wil van der Aalst & TU/e (use only with permission & acknowledgements)

Process Mining: Data Science in Act ion

Data Science and Big Data

prof.dr.ir. Wil van der Aalstwww.processmining.org

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Wil van der Aalst & TU/e (use only with permission & acknowledgements)

Data is the new oil!

In the last 10 minutes we generated more

than from prehistoric times until 2003

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Wil van der Aalst & TU/e (use only with permission & acknowledgements)

We are all generating event data!

taking the train

refueling your car

buying a coffee

adjusting the temperature

getting a spee

sending

making an a

making a phone callw

this

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Wil van der Aalst & TU/e (use only with permission & acknowledgements)

GPS

Proximity sensor

Ambient l ight sensor

Accele

Magnetomet

Gyroscopic senso

Touchscreen

Camera (front)

Camera (back)

Bluetooth

Finger-p

M

GSM/HSDPA/LTE

14+ sensors

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Internet of Events

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Internet of Events: 4 sources of event da

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Internet of Events: 4 sources of event da

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Internet of Events: 4 sources of event da

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Internet of Events: 4 sources of event da

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Wil van der Aalst & TU/e (use only with permission & acknowledgements)Wil van der Aalst & TU/e (use only with permission & acknowledgements)

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Moo

Gordon E. M

Components

Circui ts, Elec1965.Diagram by Wgsimon/CC BY 3.0

Other e

Compu

Capaci

Bytes p

220= 1.048.576x in 40 y

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Wil van der Aalst & TU/e (use only with permission & acknowledgements)

Question

40 years ag

approximathours to go

Eindhoven

Amsterdam

How long w

today if tran

technology

followed Mo

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Wil van der Aalst & TU/e (use only with permission & acknowledgements)

Answer

1.5 x 60 x 60 / 220 =

0 00515 s

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Wil van der Aalst & TU/e (use only with permission & acknowledgements)

Question

40 years ago

approximateto go from A

to New York

How long wotoday if trans

technology w

followed Mo

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Wil van der Aalst & TU/e (use only with permission & acknowledgements)

Answer

7 x 60 x 60 / 220 = 0.0240 secon

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Wil van der Aalst & TU/e (use only with permission & acknowledgements)

Question

40 years ago

approximateliters of petr

around the w

How much p

it take today

transportatio

technology w

fol lowed Moo

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Wil van der Aalst & TU/e (use only with permission & acknowledgements)

Answer

4000 / 220 = 0.0038 liters

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Wil van der Aalst & TU/e (use only with permission & acknowledgements)

Drowning in data

How

extrac

value event d

4 V' f Bi D t

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Wil van der Aalst & TU/e (use only with permission & acknowledgements)

4 V's of Big Data

VERACITYVELOCITYVARIETYVOLUME

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Wil van der Aalst & TU/e (use only with permission & acknowledgements)

Data does not have to be "Big" to be chal

Need for data scien

Data anaquestion

everywhe

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Wil van der Aalst & TU/e (use only with permission & acknowledgements)

A data scientist is able to

analyze, and interpret dat

variety of sources (socialinteraction, business proc

cyber-physical systems).

Turning data into

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Wil van der Aalst & TU/e (use only with permission & acknowledgements)

Four generic

data science

questions

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Wil van der Aalst & TU/e (use only with permission & acknowledgements)

What

happened?

#1

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Wil van der Aalst & TU/e (use only with permission & acknowledgements)

Why did

it happen?

#2

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Wil van der Aalst & TU/e (use only with permission & acknowledgements)

What will

happen?

#3

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Wil van der Aalst & TU/e (use only with permission & acknowledgements)

What is

the best that

can happen?

#4

Wh d i h

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Wil van der Aalst & TU/e (use only with permission & acknowledgements)

Can we predict

waiting times?

Why do patients have

to wait so long?

How can we

costs?

How much staff is

needed tomorrow?

Do doctors follow the

guidelines?

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Wil van der Aalst & TU/e (use only with permission & acknowledgements)

Why and when doX-ray machines

malfunction?

Which componentsshould be replaced?

How are X-ray

machines really used?

Can w

that the

will bre

next

Wh

ne

imfrom the organizational level

to the hardware/software level

Data science skills

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needed to answer

such questions

Wil van der Aalst & TU/e (use only with permission & acknowledgements)

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Wil van der Aalst & TU/e (use only with permission & acknowledgements)

DSC/e

http://www.tue.nl/

It is the process s

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It is the process s

In the end i t is th

that matters (adata or the

Not jus

and

but e

p

P t i i d t i

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Wil van der Aalst & TU/e (use only with permission & acknowledgements)

Process-centric view on data scien

Understand and improve "care

flows" in a hospital by intelligently

using event data scattered over

hundreds of database tables w ith

patient data.

Understand and improve

and performance of X-ra

in the field using teraby

level event data col lecte

remote services ne

F f thi

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Wil van der Aalst & TU/e (use only with permission & acknowledgements)

Focus of this course

P i i

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Wil van der Aalst & TU/e (use only with permission & acknowledgements)

Process mining use cases

What is the process that people re

follow?

Where are the bottlenecks in my

process?

Where do people (or machines) d

from the expected or idealized pro

M f

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Wil van der Aalst & TU/e (use only with permission & acknowledgements)

Many more use cases for process m

What are the "highways" in my process?

What factors are influencing a bottlenec

Can we predict problems (delay, deviatio

etc.) for running cases?

Can we recommend countermeasures? How to redesign the process / organizat

machine?

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Process Mining: Data Science in Part I: Preliminaries Part III: Beyond Process Discovery

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Wil van der Aalst & TU/e (use only with permission & acknowledgements)

Chapter 2Process Modeling and

Analysis

Chapter 3Data Mining

Part II: From Event Logs to Process Models

Chapter 4

Getting the Data

Chapter 5

Process Discovery: AnIntroduction

Chapter 6

Advanced ProcessDiscovery Techniques

Chapter 7Conformance

Checking

Chapter 8Mining Additional

Perspectives

Part IV: Putting Process Mining to W

Chapter 10

Tool Support

Chapter 11

Analyzing LasagnaProcesses

Part V: Reflection

Chapter 13Cartography and

Navigation

Chapter 14Epilogue

Chapter 1Introduction

Wil van der Aalst & TU/e (use only with permission & acknowledgements)