This Workshop will provide understanding to students for Process Mining: Data Science in Action" by Wil van der Aalst is a comprehensive guide that bridges the gap between business process modeling and business intelligence, positioning process mining within the broader context of data science. The second edition, published in 2016, expands upon the original with over 150 pages of new material, including discussions on data quality, inductive mining techniques, and alignments. The book is structured into six parts:
Introduction: Provides an overview of data science and introduces process mining as a crucial link between data analysis and business process management.
Preliminaries: Covers the fundamentals of business process modeling and data mining, laying the groundwork for understanding process mining techniques.
From Event Logs to Process Models: Focuses on the extraction of data from event logs and introduces both basic and advanced process discovery methods.
Beyond Process Discovery: Explores topics such as conformance checking, analyzing additional perspectives like organizational and time aspects, and operational support.
Putting Process Mining to Work: Offers practical guidance on applying process mining in real-world scenarios, including an introduction to the open-source tool ProM and various commercial products.
Reflection and Outlook: Reflects on the material presented and discusses key challenges and future directions in the field.
This book serves as a valuable resource for business process analysts, consultants, process managers, graduate students, and researchers in business process management. It provides a self-contained and comprehensive overview of process mining, from foundational concepts to practical applications.
Date, Time & Venue of the Event:
- 24-Feb-2025, 02:00 pm, DBUU Campus
Event Coordinator
- Charu Sharma- 8351051370
Contact Person:
- Charu Sharma- 8351051370
AIM of the Event:
This study aims to explore the practical application of data science, from fundamental concepts to real-world project execution. It covers key methodologies, tools, and techniques used in data-driven decision-making. The research will focus on the data science lifecycle, including problem formulation, data collection, preprocessing, analysis, model building, evaluation, and deployment. Additionally, it will highlight case studies and best practices to bridge the gap between theoretical knowledge and industry applications. The objective is to provide a comprehensive understanding of how data science can drive innovation and efficiency across various domains.
Guest/Speakers of the Event (If any):
| Name | Designation | Affiliation | Short Profile |
|---|---|---|---|
| Dr. Sugandhi Malhotra | Program Director- Tech, ImaginXP-CollegeDekho | N/A | NA |