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Process Mining - Chapter 10 - Tool Support

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.

Business◦Technology◦
Related topics:
Business Intelligence•Data Mining Insights•
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Chapter 10 Tool Support prof.dr.ir. Wil van der Aalst www.processmining.org
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
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
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.
Example: Pentaho www.pentaho.com PAGE 4
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
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
Screenshot of ProM 5.2 PAGE 7
Screenshot of ProM 6 (based on handover of work) PAGE 8
ProM 6: α miner PAGE 9
ProM 6: Social network analyzer PAGE 10
Example plug-ins in ProM 6 (see book and website) PAGE 11
Some process mining tools PAGE 12
Futura Reflect (process view) (also embedded in BPM|one) PAGE 13
Futura Reflect (social network) PAGE 14
Loading and converting event logs • XESame, Nitro, ProMimport PAGE 15