PAGE 0

BPM Round Table

Visual Analytics

TU/e, 28 maart 2011

PAGE 1

Programma

15:50 - 16:00 ontvangst met koffie en thee

16:00 - 16:05 opening

16:05 - 16:20 prof.dr. Wil van der AalstVisual Analytics, Business Unintelligence, en Process Mining

16:20 - 17:05 prof.dr.ir. Jack van Wijk (TU/e)Informatievisualisatie en Visual Analytics

17:05 - 17:50 dr. Erik-Jan van der Linden (MagnaView)De waarde van uw data vergroot

17:50 - 18:00 afsluiting

18:00 - 19:00 borrel

Visual Analytics, Business Unintelligence, Process Mining

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

Some definitions

PAGE 3

Business Process Management (BPM) is the discipline that combines knowledge from information technology and knowledge from management sciences and applies this to operational business processes.

Visual analytics combines automated analysis with interactive visualizations for an effective understanding of situations in the context of large data sets.

The goal of process mining is to use event data to extract process-related information, e.g., to automatically discover a process model by observing events recorded by some information system.

data-related

questions

process-related

questions

process mining

visualization

visual analytics

data mining

PAGE 4Data Mining

Smoker

Drinker

Weight

Short(91/10)

YesNo

Long(30/1)

NoYes

Long(150/20)

Short(321/25)

<81.5 ≥81.5

Process Mining =

Process Analysis

start register initial conditions

check_Aneeded?

check_A

modify conditions

check_Bneeded?

check_B

check_Cneeded?

check_C

assesrisk

declinec1

c2

c3

c4

c5

c6

c7

c8

c9

c10

c11

c12

c13

makeoffer

handleresponse

handlepayment

send insurance

documents

timeout1 timeout2 withdraw offer

c14 c15 c16

c17

(RM,RD)(RM,RD)(E,SD) (E,RD)

(SM,SD) (E,SD)(E,FD)

(E,SD)

(E,SD)

(YE,RD)

(YE,RD)

(FE,FD)

(RM,RD)

+

PAGE 5

The World's Technological Capacity to Store, Communicate, and Compute Information by Martin Hilbert and Priscila López (DOI 10.1126/science.1200970)

Challenge:Making sense of low level events

PAGE 6

Challenge:Making process models as good as maps

PAGE 7

• Color/size of nodes and connections• Abstraction/aggregation• Positioning of elements• Different maps for different purposes

Challenge:Seamless zoom

PAGE 8

Fuzzy miner in ProM

PAGE 9

Social network miner in ProM

PAGE 10

Challenge:Breathing life into process models

PAGE 11

Example: “Business Process Movies”

PAGE 12

Beyond Business Unintelligence

PAGE 13

PAGE 14

PAGE 15

so …

Process Mining & BPM

can benefit from

Visual Analytics

PAGE 16

Speakers

Prof.dr.ir. Jack van Wijk

Information Visualization & Visual Analytics

Dr. Erik-Jan van der Linden

Visual Analytics in de praktijk -Van data naar waarde