This document discusses tool support for process mining. It introduces the process mining tool ProM, which supports all the techniques discussed in the book and slides. ProM has a pluggable architecture and the major differences between versions 5.2 and 6 are highlighted. Screenshots of the ProM user interface are provided. Example plug-ins in ProM 6 for the alpha miner and social network analyzer are described. Other process mining tools mentioned include Futura Reflect, which can show process views and social networks, and tools for loading and converting event logs like XESame, Nitro, and ProMimport.

1. Chapter 10
Tool Support
prof.dr.ir. Wil van der Aalst
www.processmining.org

2. Overview
Chapter 1
Introduction
Part I: Preliminaries
Chapter 2 Chapter 3
Process Modeling and Data Mining
Analysis
Part II: From Event Logs to Process Models
Chapter 4 Chapter 5 Chapter 6
Getting the Data Process Discovery: An Advanced Process
Introduction Discovery Techniques
Part III: Beyond Process Discovery
Chapter 7 Chapter 8 Chapter 9
Conformance Mining Additional Operational Support
Checking Perspectives
Part IV: Putting Process Mining to Work
Chapter 10 Chapter 11 Chapter 12
Tool Support Analyzing “Lasagna Analyzing “Spaghetti
Processes” Processes”
Part V: Reflection
Chapter 13 Chapter 14
Cartography and Epilogue
Navigation
PAGE 1

3. Business Intelligence?
• “BI is a set of methodologies, processes,
architectures, and technologies that transform raw
data into meaningful and useful information used to
enable more effective strategic, tactical, and
operational insights and decision making”
• Examples of products:
IBM Cognos Business Intelligence (IBM), Oracle Business Intelligence
(Oracle), SAP BusinessObjects (SAP), WebFOCUS (Information
Builders), MS SQL Server (Microsoft), MicroStrategy (MicroStrategy),
NovaView (Panorama Software), QlikView (QlikTech), SAS Enterprise
Business Intelligence (SAS), TIBCO Spotfire Analytics (TIBCO),
Jaspersoft (Jaspersoft), and Pentaho BI Suite (Pentaho).
PAGE 2

4. Typical functionality
• ETL (Extract, Transform, and Load).
• Ad-hoc querying.
• Reporting.
• Interactive dashboards
• Alert generation. all iPhone 4G sales
in region West in the
fourth quarter of 2011
sales by product
iPhone 4G
iPod nano
N
Three dimensional
or t
th
Ea
OLAP cube containing sales iPod classic
s
n
So
o
data. Each cell refers to all
gi
ut
re
W
h
sales of a particular product Q1 Q2 Q3 Q4
es
by
t
in a particular region and
s
le
sales by quarter
sa
in a particular period. For
each cell the BI product can
compute metrics such as the
number of items sold or the
PAGE 3
total value.

5. Example: Pentaho
www.pentaho.com
PAGE 4

6. Business Unintelligence
• No real process orientation.
• Only simple views on event data.
• Focus on reporting and monitoring of KPIs.
Data mining ≠ process mining
• Data mining tools provide more “intelligent
functionality” than BI tools, but are also not process-
centric.
• See for example WEKA (Waikato Environment for
Knowledge Analysis, weka.wikispaces.com) and R
(www.r-project.org).
PAGE 5

7. ProM
• www.processmining.org
• ProM supports all of the techniques mentioned in
book and on slides!
• Pluggable architecture.
• Major differences between ProM 5.2 (and earlier) and
ProM 6.
PAGE 6

8. Screenshot of ProM 5.2
PAGE 7

9. Screenshot of ProM 6
(based on handover of work)
PAGE 8

10. ProM 6: α miner
PAGE 9

11. ProM 6: Social network analyzer
PAGE 10

12. Example plug-ins in ProM 6
(see book and website)
PAGE 11

13. Some process mining tools
PAGE 12

14. Futura Reflect (process view)
(also embedded in BPM|one)
PAGE 13

15. Futura Reflect
(social network)
PAGE 14

16. Loading and converting event logs
• XESame, Nitro, ProMimport
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