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