Chapter 10Tool Support

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

Overview

PAGE 1

Part I: Preliminaries

Chapter 2 Process Modeling and Analysis

Chapter 3Data Mining

Part II: From Event Logs to Process Models

Chapter 4 Getting the Data

Chapter 5 Process Discovery: An Introduction

Chapter 6 Advanced Process Discovery Techniques

Part III: Beyond Process Discovery

Chapter 7 Conformance Checking

Chapter 8 Mining Additional Perspectives

Chapter 9 Operational Support

Part IV: Putting Process Mining to Work

Chapter 10 Tool Support

Chapter 11 Analyzing “Lasagna Processes”

Chapter 12 Analyzing “Spaghetti Processes”

Part V: Reflection

Chapter 13Cartography and Navigation

Chapter 14Epilogue

Chapter 1 Introduction

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.

PAGE 3

iPhone 4G

iPod nano

iPod classic

Q1 Q2 Q3 Q4

sales by quarter

sale

s by

pro

duct

West

South

East

North

sales

by re

gion

all iPhone 4G sales in region West in the

fourth quarter of 2011

Three dimensionalOLAP cube containing salesdata. Each cell refers to allsales of a particular productin a particular region andin a particular period. Foreach cell the BI product cancompute metrics such as thenumber of items sold or thetotal value.

Example: Pentahowww.pentaho.com

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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).

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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

PAGE 8(based on handover of work)

ProM 6: α miner

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ProM 6: Social network analyzer

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Example plug-ins in ProM 6(see book and website)

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Some process mining tools

PAGE 12

Futura Reflect (process view)(also embedded in BPM|one)

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Futura Reflect(social network)

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Loading and converting event logs

• XESame, Nitro, ProMimport

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